Various rumors and assumptions have circulated about the COVID 19 immunization, making it a heated subject of discussion in India. This prompted a reaction from the countrys populace, who During the course of favorable, negative, and neutral evaluations, tweets and retweets on twitter. The number of these tweets are a jumble of unstructured data. The goal of this study is to have the statistics justify feeling implied by it. The purpose of this study is to take advantage of twitters massive data pool and extract insights that have the implications that can be drawn from it. Comprehensive research on the peoples feelings may help us arrive at a fair familiarity with the population at larges point of view toward preventing disease by vaccination. Dataset taken into consideration for vaccination related tweets are collected for study. From 2020 to 2021, including a data mining of 16,05,152 tweets related to vaccination. Ms. Tanzeela Qureshi | Dr. Mohit Singh Tomar | Dr. Ritu Shrivastava "An Assessment of Sentiment Analysis of Covid-19 Tweets" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-5 , October 2023, URL: https://www.ijtsrd.com/papers/ijtsrd59976.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/59976/an-assessment-of-sentiment-analysis-of-covid19-tweets/ms-tanzeela-qureshi
CATEGORIZING 2019-N-COV TWITTER HASHTAG DATA BY CLUSTERINGijaia
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety,
Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
Categorizing 2019-n-CoV Twitter Hashtag Data by Clusteringgerogepatton
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety, Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
CATEGORIZING 2019-N-COV TWITTER HASHTAG DATA BY CLUSTERINGgerogepatton
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety, Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
Analyzing sentiment dynamics from sparse text coronavirus disease-19 vaccina...IJECEIAES
Social media platforms enable people exchange their thoughts, reactions, emotions regarding all aspects of their lives. Therefore, sentiment analysis using textual data is widely practiced field. Due to large textual content available on social media, sentiment analysis is usually considered a text classification task. The high feature dimension is an important issue that needs to be resolved by examining text meaningfully. The proposed study considers a case study of coronavirus (COVID) vaccination to conclude public opinions about prospects for vaccination. Text corpus of tweets is collected, published between December 12, 2020, and July 13, 2021 is considered. The proposed model is developed considering phase-by-phase data analysis process, followed by an assessment of important information about the collected tweets on coronavirus disease (COVID-19) vaccine using two sentiment analyzer methods and probabilistic models for validation and knowledge analysis. The result indicated that public sentiment is more positive than negative. The study also presented statistics of trends in vaccination progress in the top countries from early 2021 to July 2021. The scope of study is enormous regarding sentiment analysis based on keyword and document modeling. The proposed work offers an effective mechanism for a decision-making system to understand public opinion and accordingly assists policymakers in health measures and vaccination campaigns.
PANDEMIC INFORMATION DISSEMINATION WEB APPLICATION: A MANUAL DESIGN FOR EVERYONEijcsitcejournal
The aim of this research is to generate a web application from an inedited methodology with a series of
instructions indicating the coding in a flow diagram. The primary purpose of this methodology is to aid
non-profits in disseminating information regarding the COVID-19 pandemic, so that users can share vital
and up-to-date information. This is a functional design, and a series of screenshots demonstrating its
behaviour is presented below. This unique design arose from the necessity to create a web application for
an information dissemination platform; it also addresses an audience that does not have programming
knowledge. This document uses the scientific method in its writing. The authors understand that there is a
similar design in the bibliography; therefore, the differences between the designs are described herein; it
is very important to point out that this proposal can be taken as an alternative to the design of any web
application.
Twitter Based Sentimental Analysis of Impact of COVID-19 on Economy using Naï...CSCJournals
COVID-19 outbreak brought unprecedented changes to people’s lives and made significant impact on the US and world economy. It wrought havoc on livelihood, businesses and ultimately the economy. Understanding how the sentiment on economy is changing and main factors that drives the change will help the public to make sense of the impact and generating relief measures. In this paper we present a novel Naïve Bayes model using a word-based training approach to perform the analysis and determine the sentiment of Twitter posts. The novelty of this methodology is that we use labelled set of words to classify the tweets to perform sentimental analysis as opposed to the more expensive methods of manually classifying the tweets. We then perform analysis on the resulting labelled tweets to observe the trend of economy from February 2020 to July 2020 and determine how COVID-19 impacted the economy based on what people posted on Twitter. We found our data was largely inclined towards negative sentiment indicating that the economy had been largely negatively impacted as a result of COVID-19. Further, we correlate the sentiment with the stock market index aka Dow Jones Industrial Average (DJIA) because stock market movement closely mirrors the economic sentiment and is shown as one of the main factors influencing people's attitude change from our sentimental analysis. We found strong correlation between the two, indicating stock market change is one of the driving factors behind people's opinion change about economy during pandemic. This work proposed and tested a generic lower-cost text-based model to analysis generic public’s opinion about an event which can be adopted to analyze other topics.
Pfizer VS Moderna Case Study - PresentationBytesview
In this case study, we will examine all tweets related to covid vaccines using sentiment analysis to evaluate the public sentiments towards the COVID-19 vaccines.
CATEGORIZING 2019-N-COV TWITTER HASHTAG DATA BY CLUSTERINGijaia
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety,
Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
Categorizing 2019-n-CoV Twitter Hashtag Data by Clusteringgerogepatton
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety, Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
CATEGORIZING 2019-N-COV TWITTER HASHTAG DATA BY CLUSTERINGgerogepatton
Unsupervised machine learning techniques such as clustering are widely gaining use with the recent increase in social communication platforms like Twitter and Facebook. Clustering enables the finding of patterns in these unstructured datasets. We collected tweets matching hashtags linked to COVID-19 from a Kaggle dataset. We compared the performance of nine clustering algorithms using this dataset. We evaluated the generalizability of these algorithms using a supervised learning model. Finally, using a selected unsupervised learning algorithm we categorized the clusters. The top five categories are Safety, Crime, Products, Countries and Health. This can prove helpful for bodies using large amount of Twitter data needing to quickly find key points in the data before going into further classification.
Analyzing sentiment dynamics from sparse text coronavirus disease-19 vaccina...IJECEIAES
Social media platforms enable people exchange their thoughts, reactions, emotions regarding all aspects of their lives. Therefore, sentiment analysis using textual data is widely practiced field. Due to large textual content available on social media, sentiment analysis is usually considered a text classification task. The high feature dimension is an important issue that needs to be resolved by examining text meaningfully. The proposed study considers a case study of coronavirus (COVID) vaccination to conclude public opinions about prospects for vaccination. Text corpus of tweets is collected, published between December 12, 2020, and July 13, 2021 is considered. The proposed model is developed considering phase-by-phase data analysis process, followed by an assessment of important information about the collected tweets on coronavirus disease (COVID-19) vaccine using two sentiment analyzer methods and probabilistic models for validation and knowledge analysis. The result indicated that public sentiment is more positive than negative. The study also presented statistics of trends in vaccination progress in the top countries from early 2021 to July 2021. The scope of study is enormous regarding sentiment analysis based on keyword and document modeling. The proposed work offers an effective mechanism for a decision-making system to understand public opinion and accordingly assists policymakers in health measures and vaccination campaigns.
PANDEMIC INFORMATION DISSEMINATION WEB APPLICATION: A MANUAL DESIGN FOR EVERYONEijcsitcejournal
The aim of this research is to generate a web application from an inedited methodology with a series of
instructions indicating the coding in a flow diagram. The primary purpose of this methodology is to aid
non-profits in disseminating information regarding the COVID-19 pandemic, so that users can share vital
and up-to-date information. This is a functional design, and a series of screenshots demonstrating its
behaviour is presented below. This unique design arose from the necessity to create a web application for
an information dissemination platform; it also addresses an audience that does not have programming
knowledge. This document uses the scientific method in its writing. The authors understand that there is a
similar design in the bibliography; therefore, the differences between the designs are described herein; it
is very important to point out that this proposal can be taken as an alternative to the design of any web
application.
Twitter Based Sentimental Analysis of Impact of COVID-19 on Economy using Naï...CSCJournals
COVID-19 outbreak brought unprecedented changes to people’s lives and made significant impact on the US and world economy. It wrought havoc on livelihood, businesses and ultimately the economy. Understanding how the sentiment on economy is changing and main factors that drives the change will help the public to make sense of the impact and generating relief measures. In this paper we present a novel Naïve Bayes model using a word-based training approach to perform the analysis and determine the sentiment of Twitter posts. The novelty of this methodology is that we use labelled set of words to classify the tweets to perform sentimental analysis as opposed to the more expensive methods of manually classifying the tweets. We then perform analysis on the resulting labelled tweets to observe the trend of economy from February 2020 to July 2020 and determine how COVID-19 impacted the economy based on what people posted on Twitter. We found our data was largely inclined towards negative sentiment indicating that the economy had been largely negatively impacted as a result of COVID-19. Further, we correlate the sentiment with the stock market index aka Dow Jones Industrial Average (DJIA) because stock market movement closely mirrors the economic sentiment and is shown as one of the main factors influencing people's attitude change from our sentimental analysis. We found strong correlation between the two, indicating stock market change is one of the driving factors behind people's opinion change about economy during pandemic. This work proposed and tested a generic lower-cost text-based model to analysis generic public’s opinion about an event which can be adopted to analyze other topics.
Pfizer VS Moderna Case Study - PresentationBytesview
In this case study, we will examine all tweets related to covid vaccines using sentiment analysis to evaluate the public sentiments towards the COVID-19 vaccines.
Stock market prediction using Twitter sentiment analysisIJRTEMJOURNAL
In a study, it was investigated relationship among stock market movement and Tweeter feed
content. We are expecting to see if there is connection among sentiment information extracted from the Tweets
using a Vader in predicting movements of stock prices. As a result it was obtained strong positive correlation with
a coefficient of correlation to be 0.7815.
Stock market prediction using Twitter sentiment analysisjournal ijrtem
ABSTRACT : In a study, it was investigated relationship among stock market movement and Tweeter feed content. We are expecting to see if there is connection among sentiment information extracted from the Tweets using a Vader in predicting movements of stock prices. As a result it was obtained strong positive correlation with a coefficient of correlation to be 0.7815.
KEYWORDS : correlation, financial market, polarity, sentiment analysis, tweets
Thai COVID-19 patient clustering for monitoring and prevention: data mining t...IAESIJAI
This research aims to optimize emerging infectious disease monitoring techniques in Thailand, which will be extremely valuable to the government, doctors, police, and others involved in understanding the seriousness of the spread of novel coronavirus to improve government policies, decisions, medical facilities, treatment. The data mining techniques included cluster analysis using K-means clustering. The infection data were obtained from the open data of the digital government development agency, Thailand. The dataset consisted of 1,893,941 cumulative cases from January 2020 to October 2021 of the outbreak. The results from clustering consisted of 8 groups. Clustering results determined the three largest, three medium-sized, and the two most minor numbers of infected people, respectively. These clusters represent their activities, namely touching an infected person and checking themselves. The components of emerging diseases in Thailand are closely related to waves, gender, age, nationality, career, behavioral risk, and region. The province of onset was mainly in Bangkok and its vicinity or central Thailand, as well as industrial areas. Adult workers aged 19 to 27 years and 43 to 54 years or over were seeds of new infection sources.
Clustering analysis on news from health OSINT data regarding CORONAVIRUS-COVI...ALexandruDaia1
Our primarly goal was to detect clusters via gensim libraries in news data consisting ofinformation regarding health and threats. We identified clusters for the periodscorresponding: i) Jannuary 2006 until the end of 2019, as December 2019 is considered thefirst month in which information about CORONVIRUS COVID-19 was made public; ii)between the 1st of Jannuary 2019 and 31st December 2019; and iii) between the 31st ofDecember 2019 and the 14th of April 2020. We conducted experiments using naturallanguage on open source intelligence data offered generously by brica.de, a providerspecialized in Business Risk Intelligence & Cyberthreat Awareness.
Intelligent Models for predicting diseases whether building a model to help the doctor or even preventing its spread in an area globally, is increasing day by day. Here we present a noble approach to predict the disease prone area using the power of Text Analysis and Machine Learning. Epidemic Search model using the power of the social network data analysis and then using this data to provide a probability score of the spread and to analyse the areas whether going to suffer from any epidemic spread-out, is the main focus of this work. We have tried to analyse and showcase how the model with different kinds of pre-processing and algorithms predict the output. We have used the combination of words-n grams, word embeddings and TFIDF with different data mining and deep learning algorithms like SVM, Naïve Bayes and RNN-LSTM. Naïve Bayes with TF-IDF performed better in comparison to others.
EPIDEMIC OUTBREAK PREDICTION USING ARTIFICIAL INTELLIGENCEijcsit
Intelligent Models for predicting diseases whether building a model to help the doctor or even preventing its spread in an area globally, is increasing day by day. Here we present a noble approach to predict the disease prone area using the power of Text Analysis and Machine Learning. Epidemic Search model using the power of the social network data analysis and then using this data to provide a probability score of the spread and to analyse the areas whether going to suffer from any epidemic spread-out, is the main focus of this work. We have tried to analyse and showcase how the model with different kinds of pre-processing and algorithms predict the output. We have used the combination of words-n grams, word embeddings and TFIDF with different data mining and deep learning algorithms like SVM, Naïve Bayes and RNN-LSTM. Naïve Bayes with TF-IDF performed better in comparison to others.
With the spread of social media platforms and the proliferation of misleading news, misinformation
detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic,
many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these
fake news, many works have been done on misinformation detection using machine learning and sentiment
analysis in the English language. However, misinformation detection research in the Arabic language on
social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19
related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using
multiple phases of preprocessing techniques before applying different machine learning classification
algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets
achieving 93% best overall accuracy of the model in detecting misinformation. We further build another
dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of
claims. Results show that the combination of machine learning techniques and linguistic analysis achieves
the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
COMBINING MACHINE LEARNING AND SEMANTIC ANALYSIS FOR EFFICIENT MISINFORMATION...ijcsit
With the spread of social media platforms and the proliferation of misleading news, misinformation
detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic,
many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these
fake news, many works have been done on misinformation detection using machine learning and sentiment
analysis in the English language. However, misinformation detection research in the Arabic language on
social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19
related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using
multiple phases of preprocessing techniques before applying different machine learning classification
algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets
achieving 93% best overall accuracy of the model in detecting misinformation. We further build another
dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of
claims. Results show that the combination of machine learning techniques and linguistic analysis achieves
the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
An Overview on the Use of Data Mining and Linguistics Techniques for Building...ijcsit
The usage of Online Social Networks (OSN), such as Facebook and Twitter are becoming more and more
popular in order to exchange and disseminate news and information in real-time. Twitter in particular
allows the instant dissemination of short messages in the form of microblogs to followers. This Survey
reviews literature to explore and examine the usage of how OSNs, such as the microblogging tool Twitter,
can help in the detection of spreading epidemics. The paper highlights significant challenges in the field of
Natural Language Processing (NLP) when using microblog based Early Disease Detection Systems. For
instance, microblogging data is an unstructured collection of short messages (140 characters in Twitter),
with noise and non-standard use of the English language. Hence, research is currently exploring the field
of linguistics in order to determine the semantics of the text and uses data mining techniques in order to
extract useful information for disease spread detection. Furthermore, the survey discusses applications and
existing early disease detection systems based on OSNs and outlines directions for future research on
improving such systems based on a combination of linguistics methods, data mining techniques and
recommendation systems.
Global Pulse: Mining Indonesian Tweets to Understand Food Price Crises copyUN Global Pulse
Sudden increases in the price of staple foodstuffs like rice can push whole families below the poverty line and cause regional economic instability; these changes can happen rapidly but food price statistics are generally published only monthly or even less frequently.
This project, in collaboration with the Indonesian Ministry of Development Planning, UNICEF and WFP in Indonesia seeks to use social media analysis to provide real-time information from the population that could enable faster responses to food price increases in the form of social protection policies. Global Pulse analysed tweet volumes relevant to food and fuel between March 2011 and April 2013 and found a significant correlation, suggesting that even potential (rather than realised) fuel price rises affect people’s perceptions of food security. Researchers also found a relationship between retrospective official food inflation statistics and the number of tweets referencing food price increases.
http://www.unglobalpulse.org/social-media-social-protection-indonesia
ANALYSIS OF TOPIC MODELING WITH UNPOOLED AND POOLED TWEETS AND EXPLORATION OF...IJCSEA Journal
In this digital era, social media is an important tool for information dissemination. Twitter is a popular social media platform. Social media analytics helps make informed decisions based on people's needs and opinions. This information, when properly perceived provides valuable insights into different domains, such as public policymaking, marketing, sales, and healthcare. Topic modeling is an unsupervised algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet Allocation (LDA) topic model algorithm. We collected tweets with hashtags related to corona virus related discussions. This study compares regular LDA and LDA based on collapsed Gibbs sampling (LDAMallet) algorithms. The experiments use different data processing steps including trigrams, without trigrams, hashtags, and without hashtags. This study provides a comprehensive analysis of LDA for short text messages using un-pooled and pooled tweets. The results suggest that a pooling scheme using hashtags helps improve the topic inference results with a better coherence score.
ANALYSIS OF TOPIC MODELING WITH UNPOOLED AND POOLED TWEETS AND EXPLORATION OF...IJCSEA Journal
In this digital era, social media is an important tool for information dissemination. Twitter is a popular
social media platform. Social media analytics helps make informed decisions based on people's needs and
opinions. This information, when properly perceived provides valuable insights into different domains,
such as public policymaking, marketing, sales, and healthcare. Topic modeling is an unsupervised
algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet
Allocation (LDA) topic model algorithm. We collected tweets with hashtags related to corona virus related
discussions. This study compares regular LDA and LDA based on collapsed Gibbs sampling (LDAMallet)
algorithms. The experiments use different data processing steps including trigrams, without trigrams,
hashtags, and without hashtags. This study provides a comprehensive analysis of LDA for short text
messages using un-pooled and pooled tweets. The results suggest that a pooling scheme using hashtags
helps improve the topic inference results with a better coherence score.
International Journal of Computer Science, Engineering and Applications (IJCSEA)IJCSEA Journal
International Journal of Computer Science, Engineering and Applications (IJCSEA) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer science, Engineering and Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science, Engineering and Applications.
ANALYSIS OF TOPIC MODELING WITH UNPOOLED AND POOLED TWEETS AND EXPLORATION OF...IJCSEA Journal
In this digital era, social media is an important tool for information dissemination. Twitter is a popular
social media platform. Social media analytics helps make informed decisions based on people's needs and
opinions. This information, when properly perceived provides valuable insights into different domains,
such as public policymaking, marketing, sales, and healthcare. Topic modeling is an unsupervised
algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet
Allocation (LDA) topic model algorithm. We collected tweets with hashtags related to corona virus related
discussions. This study compares regular LDA and LDA based on collapsed Gibbs sampling (LDAMallet)
algorithms. The experiments use different data processing steps including trigrams, without trigrams,
hashtags, and without hashtags. This study provides a comprehensive analysis of LDA for short text
messages using un-pooled and pooled tweets. The results suggest that a pooling scheme using hashtags
helps improve the topic inference results with a better coherence score.
‘Six Sigma Technique’ A Journey Through its Implementationijtsrd
The manufacturing industries all over the world are facing tough challenges for growth, development and sustainability in today’s competitive environment. They have to achieve apex position by adapting with the global competitive environment by delivering goods and services at low cost, prime quality and better price to increase wealth and consumer satisfaction. Cost Management ensures profit, growth and sustainability of the business with implementation of Continuous Improvement Technique like Six Sigma. This leads to optimize Business performance. The method drives for customer satisfaction, low variation, reduction in waste and cycle time resulting into a competitive advantage over other industries which did not implement it. The main objective of this paper ‘Six Sigma Technique A Journey Through Its Implementation’ is to conceptualize the effectiveness of Six Sigma Technique through the journey of its implementation. Aditi Sunilkumar Ghosalkar "‘Six Sigma Technique’: A Journey Through its Implementation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64546.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64546/‘six-sigma-technique’-a-journey-through-its-implementation/aditi-sunilkumar-ghosalkar
Edge Computing in Space Enhancing Data Processing and Communication for Space...ijtsrd
Edge computing, a paradigm that involves processing data closer to its source, has gained significant attention for its potential to revolutionize data processing and communication in space missions. With the increasing complexity and data volume generated by modern space missions, traditional centralized computing approaches face challenges related to latency, bandwidth, and security. Edge computing in space, involving on board processing and analysis of data, offers promising solutions to these challenges. This paper explores the concept of edge computing in space, its benefits, applications, and future prospects in enhancing space missions. Manish Verma "Edge Computing in Space: Enhancing Data Processing and Communication for Space Missions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64541.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/64541/edge-computing-in-space-enhancing-data-processing-and-communication-for-space-missions/manish-verma
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a coefficient of correlation to be 0.7815.
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ABSTRACT : In a study, it was investigated relationship among stock market movement and Tweeter feed content. We are expecting to see if there is connection among sentiment information extracted from the Tweets using a Vader in predicting movements of stock prices. As a result it was obtained strong positive correlation with a coefficient of correlation to be 0.7815.
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Clustering analysis on news from health OSINT data regarding CORONAVIRUS-COVI...ALexandruDaia1
Our primarly goal was to detect clusters via gensim libraries in news data consisting ofinformation regarding health and threats. We identified clusters for the periodscorresponding: i) Jannuary 2006 until the end of 2019, as December 2019 is considered thefirst month in which information about CORONVIRUS COVID-19 was made public; ii)between the 1st of Jannuary 2019 and 31st December 2019; and iii) between the 31st ofDecember 2019 and the 14th of April 2020. We conducted experiments using naturallanguage on open source intelligence data offered generously by brica.de, a providerspecialized in Business Risk Intelligence & Cyberthreat Awareness.
Intelligent Models for predicting diseases whether building a model to help the doctor or even preventing its spread in an area globally, is increasing day by day. Here we present a noble approach to predict the disease prone area using the power of Text Analysis and Machine Learning. Epidemic Search model using the power of the social network data analysis and then using this data to provide a probability score of the spread and to analyse the areas whether going to suffer from any epidemic spread-out, is the main focus of this work. We have tried to analyse and showcase how the model with different kinds of pre-processing and algorithms predict the output. We have used the combination of words-n grams, word embeddings and TFIDF with different data mining and deep learning algorithms like SVM, Naïve Bayes and RNN-LSTM. Naïve Bayes with TF-IDF performed better in comparison to others.
EPIDEMIC OUTBREAK PREDICTION USING ARTIFICIAL INTELLIGENCEijcsit
Intelligent Models for predicting diseases whether building a model to help the doctor or even preventing its spread in an area globally, is increasing day by day. Here we present a noble approach to predict the disease prone area using the power of Text Analysis and Machine Learning. Epidemic Search model using the power of the social network data analysis and then using this data to provide a probability score of the spread and to analyse the areas whether going to suffer from any epidemic spread-out, is the main focus of this work. We have tried to analyse and showcase how the model with different kinds of pre-processing and algorithms predict the output. We have used the combination of words-n grams, word embeddings and TFIDF with different data mining and deep learning algorithms like SVM, Naïve Bayes and RNN-LSTM. Naïve Bayes with TF-IDF performed better in comparison to others.
With the spread of social media platforms and the proliferation of misleading news, misinformation
detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic,
many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these
fake news, many works have been done on misinformation detection using machine learning and sentiment
analysis in the English language. However, misinformation detection research in the Arabic language on
social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19
related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using
multiple phases of preprocessing techniques before applying different machine learning classification
algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets
achieving 93% best overall accuracy of the model in detecting misinformation. We further build another
dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of
claims. Results show that the combination of machine learning techniques and linguistic analysis achieves
the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
COMBINING MACHINE LEARNING AND SEMANTIC ANALYSIS FOR EFFICIENT MISINFORMATION...ijcsit
With the spread of social media platforms and the proliferation of misleading news, misinformation
detection within microblogging platforms has become a real challenge. During the Covid-19 pandemic,
many fake news and rumors were broadcasted and shared daily on social media. In order to filter out these
fake news, many works have been done on misinformation detection using machine learning and sentiment
analysis in the English language. However, misinformation detection research in the Arabic language on
social media is limited. This paper introduces a misinformation verification system for Arabic COVID-19
related news using an Arabic rumors dataset on Twitter. We explored the dataset and prepared it using
multiple phases of preprocessing techniques before applying different machine learning classification
algorithms combined with a semantic analysis method. The model was applied on 3.6k annotated tweets
achieving 93% best overall accuracy of the model in detecting misinformation. We further build another
dataset of Covid-19 related claims in Arabic to examine how our model performs with this new set of
claims. Results show that the combination of machine learning techniques and linguistic analysis achieves
the best scores reaching 92% best accuracy in detecting the veracity of sentences of the new dataset.
An Overview on the Use of Data Mining and Linguistics Techniques for Building...ijcsit
The usage of Online Social Networks (OSN), such as Facebook and Twitter are becoming more and more
popular in order to exchange and disseminate news and information in real-time. Twitter in particular
allows the instant dissemination of short messages in the form of microblogs to followers. This Survey
reviews literature to explore and examine the usage of how OSNs, such as the microblogging tool Twitter,
can help in the detection of spreading epidemics. The paper highlights significant challenges in the field of
Natural Language Processing (NLP) when using microblog based Early Disease Detection Systems. For
instance, microblogging data is an unstructured collection of short messages (140 characters in Twitter),
with noise and non-standard use of the English language. Hence, research is currently exploring the field
of linguistics in order to determine the semantics of the text and uses data mining techniques in order to
extract useful information for disease spread detection. Furthermore, the survey discusses applications and
existing early disease detection systems based on OSNs and outlines directions for future research on
improving such systems based on a combination of linguistics methods, data mining techniques and
recommendation systems.
Global Pulse: Mining Indonesian Tweets to Understand Food Price Crises copyUN Global Pulse
Sudden increases in the price of staple foodstuffs like rice can push whole families below the poverty line and cause regional economic instability; these changes can happen rapidly but food price statistics are generally published only monthly or even less frequently.
This project, in collaboration with the Indonesian Ministry of Development Planning, UNICEF and WFP in Indonesia seeks to use social media analysis to provide real-time information from the population that could enable faster responses to food price increases in the form of social protection policies. Global Pulse analysed tweet volumes relevant to food and fuel between March 2011 and April 2013 and found a significant correlation, suggesting that even potential (rather than realised) fuel price rises affect people’s perceptions of food security. Researchers also found a relationship between retrospective official food inflation statistics and the number of tweets referencing food price increases.
http://www.unglobalpulse.org/social-media-social-protection-indonesia
ANALYSIS OF TOPIC MODELING WITH UNPOOLED AND POOLED TWEETS AND EXPLORATION OF...IJCSEA Journal
In this digital era, social media is an important tool for information dissemination. Twitter is a popular social media platform. Social media analytics helps make informed decisions based on people's needs and opinions. This information, when properly perceived provides valuable insights into different domains, such as public policymaking, marketing, sales, and healthcare. Topic modeling is an unsupervised algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet Allocation (LDA) topic model algorithm. We collected tweets with hashtags related to corona virus related discussions. This study compares regular LDA and LDA based on collapsed Gibbs sampling (LDAMallet) algorithms. The experiments use different data processing steps including trigrams, without trigrams, hashtags, and without hashtags. This study provides a comprehensive analysis of LDA for short text messages using un-pooled and pooled tweets. The results suggest that a pooling scheme using hashtags helps improve the topic inference results with a better coherence score.
ANALYSIS OF TOPIC MODELING WITH UNPOOLED AND POOLED TWEETS AND EXPLORATION OF...IJCSEA Journal
In this digital era, social media is an important tool for information dissemination. Twitter is a popular
social media platform. Social media analytics helps make informed decisions based on people's needs and
opinions. This information, when properly perceived provides valuable insights into different domains,
such as public policymaking, marketing, sales, and healthcare. Topic modeling is an unsupervised
algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet
Allocation (LDA) topic model algorithm. We collected tweets with hashtags related to corona virus related
discussions. This study compares regular LDA and LDA based on collapsed Gibbs sampling (LDAMallet)
algorithms. The experiments use different data processing steps including trigrams, without trigrams,
hashtags, and without hashtags. This study provides a comprehensive analysis of LDA for short text
messages using un-pooled and pooled tweets. The results suggest that a pooling scheme using hashtags
helps improve the topic inference results with a better coherence score.
International Journal of Computer Science, Engineering and Applications (IJCSEA)IJCSEA Journal
International Journal of Computer Science, Engineering and Applications (IJCSEA) is an open access peer-reviewed journal that publishes articles which contribute new results in all areas of the computer science, Engineering and Applications. The journal is devoted to the publication of high quality papers on theoretical and practical aspects of computer science, Engineering and Applications.
ANALYSIS OF TOPIC MODELING WITH UNPOOLED AND POOLED TWEETS AND EXPLORATION OF...IJCSEA Journal
In this digital era, social media is an important tool for information dissemination. Twitter is a popular
social media platform. Social media analytics helps make informed decisions based on people's needs and
opinions. This information, when properly perceived provides valuable insights into different domains,
such as public policymaking, marketing, sales, and healthcare. Topic modeling is an unsupervised
algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet
Allocation (LDA) topic model algorithm. We collected tweets with hashtags related to corona virus related
discussions. This study compares regular LDA and LDA based on collapsed Gibbs sampling (LDAMallet)
algorithms. The experiments use different data processing steps including trigrams, without trigrams,
hashtags, and without hashtags. This study provides a comprehensive analysis of LDA for short text
messages using un-pooled and pooled tweets. The results suggest that a pooling scheme using hashtags
helps improve the topic inference results with a better coherence score.
Similar to An Assessment of Sentiment Analysis of Covid 19 Tweets (20)
‘Six Sigma Technique’ A Journey Through its Implementationijtsrd
The manufacturing industries all over the world are facing tough challenges for growth, development and sustainability in today’s competitive environment. They have to achieve apex position by adapting with the global competitive environment by delivering goods and services at low cost, prime quality and better price to increase wealth and consumer satisfaction. Cost Management ensures profit, growth and sustainability of the business with implementation of Continuous Improvement Technique like Six Sigma. This leads to optimize Business performance. The method drives for customer satisfaction, low variation, reduction in waste and cycle time resulting into a competitive advantage over other industries which did not implement it. The main objective of this paper ‘Six Sigma Technique A Journey Through Its Implementation’ is to conceptualize the effectiveness of Six Sigma Technique through the journey of its implementation. Aditi Sunilkumar Ghosalkar "‘Six Sigma Technique’: A Journey Through its Implementation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64546.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64546/‘six-sigma-technique’-a-journey-through-its-implementation/aditi-sunilkumar-ghosalkar
Edge Computing in Space Enhancing Data Processing and Communication for Space...ijtsrd
Edge computing, a paradigm that involves processing data closer to its source, has gained significant attention for its potential to revolutionize data processing and communication in space missions. With the increasing complexity and data volume generated by modern space missions, traditional centralized computing approaches face challenges related to latency, bandwidth, and security. Edge computing in space, involving on board processing and analysis of data, offers promising solutions to these challenges. This paper explores the concept of edge computing in space, its benefits, applications, and future prospects in enhancing space missions. Manish Verma "Edge Computing in Space: Enhancing Data Processing and Communication for Space Missions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64541.pdf Paper Url: https://www.ijtsrd.com/computer-science/artificial-intelligence/64541/edge-computing-in-space-enhancing-data-processing-and-communication-for-space-missions/manish-verma
Dynamics of Communal Politics in 21st Century India Challenges and Prospectsijtsrd
Communal politics in India has evolved through centuries, weaving a complex tapestry shaped by historical legacies, colonial influences, and contemporary socio political transformations. This research comprehensively examines the dynamics of communal politics in 21st century India, emphasizing its historical roots, socio political dynamics, economic implications, challenges, and prospects for mitigation. The historical perspective unravels the intricate interplay of religious identities and power dynamics from ancient civilizations to the impact of colonial rule, providing insights into the evolution of communalism. The socio political dynamics section delves into the contemporary manifestations, exploring the roles of identity politics, socio economic disparities, and globalization. The economic implications section highlights how communal politics intersects with economic issues, perpetuating disparities and influencing resource allocation. Challenges posed by communal politics are scrutinized, revealing multifaceted issues ranging from social fragmentation to threats against democratic values. The prospects for mitigation present a multifaceted approach, incorporating policy interventions, community engagement, and educational initiatives. The paper conducts a comparative analysis with international examples, identifying common patterns such as identity politics and economic disparities. It also examines unique challenges, emphasizing Indias diverse religious landscape, historical legacy, and secular framework. Lessons for effective strategies are drawn from international experiences, offering insights into inclusive policies, interfaith dialogue, media regulation, and global cooperation. By scrutinizing historical epochs, contemporary dynamics, economic implications, and international comparisons, this research provides a comprehensive understanding of communal politics in India. The proposed strategies for mitigation underscore the importance of a holistic approach to foster social harmony, inclusivity, and democratic values. Rose Hossain "Dynamics of Communal Politics in 21st Century India: Challenges and Prospects" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64528.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/history/64528/dynamics-of-communal-politics-in-21st-century-india-challenges-and-prospects/rose-hossain
Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in...ijtsrd
Background and Objective Telehealth has become a well known tool for the delivery of health care in Saudi Arabia, and the perspective and knowledge of healthcare providers are influential in the implementation, adoption and advancement of the method. This systematic review was conducted to examine the current literature base regarding telehealth and the related healthcare professional perspective and knowledge in the Kingdom of Saudi Arabia. Materials and Methods This systematic review was conducted by searching 7 databases including, MEDLINE, CINHAL, Web of Science, Scopus, PubMed, PsycINFO, and ProQuest Central. Studies on healthcare practitioners telehealth knowledge and perspectives published in English in Saudi Arabia from 2000 to 2023 were included. Boland directed this comprehensive review. The researchers examined each connected study using the AXIS tool, which evaluates cross sectional systematic reviews. Narrative synthesis was used to summarise and convey the data. Results Out of 1840 search results, 10 studies were included. Positive outlook and limited knowledge among providers were seen across trials. Healthcare professionals like telehealth for its ability to improve quality, access, and delivery, save time and money, and be successful. Age, gender, occupation, and work experience also affect health workers knowledge. In Saudi Arabia, healthcare professionals face inadequate expert assistance, patient privacy, internet connection concerns, lack of training courses, lack of telehealth understanding, and high costs while performing telemedicine. Conclusions Healthcare practitioners telehealth perceptions and knowledge were examined in this systematic study. Its collection of concerned experts different personal attitudes and expertise would help enhance telehealths implementation in Saudi Arabia, develop its healthcare delivery alternative, and eliminate frequent problems. Badriah Mousa I Mulayhi | Dr. Jomin George | Judy Jenkins "Assess Perspective and Knowledge of Healthcare Providers Towards Elehealth in Saudi Arabia: A Systematic Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64535.pdf Paper Url: https://www.ijtsrd.com/medicine/other/64535/assess-perspective-and-knowledge-of-healthcare-providers-towards-elehealth-in-saudi-arabia-a-systematic-review/badriah-mousa-i-mulayhi
The Impact of Digital Media on the Decentralization of Power and the Erosion ...ijtsrd
The impact of digital media on the distribution of power and the weakening of traditional gatekeepers has gained considerable attention in recent years. The adoption of digital technologies and the internet has resulted in declining influence and power for traditional gatekeepers such as publishing houses and news organizations. Simultaneously, digital media has facilitated the emergence of new voices and players in the media industry. Digital medias impact on power decentralization and gatekeeper erosion is visible in several ways. One significant aspect is the democratization of information, which enables anyone with an internet connection to publish and share content globally, leading to citizen journalism and bypassing traditional gatekeepers. Another aspect is the disruption of conventional media industry business models, as traditional organizations struggle to adjust to the decrease in advertising revenue and the rise of digital platforms. Alternative business models, such as subscription models and crowdfunding, have become more prevalent, leading to the emergence of new players. Overall, the impact of digital media on the distribution of power and the weakening of traditional gatekeepers has brought about significant changes in the media landscape and the way information is shared. Further research is required to fully comprehend the implications of these changes and their impact on society. Dr. Kusum Lata "The Impact of Digital Media on the Decentralization of Power and the Erosion of Traditional Gatekeepers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64544.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64544/the-impact-of-digital-media-on-the-decentralization-of-power-and-the-erosion-of-traditional-gatekeepers/dr-kusum-lata
Online Voices, Offline Impact Ambedkars Ideals and Socio Political Inclusion ...ijtsrd
This research investigates the nexus between online discussions on Dr. B.R. Ambedkars ideals and their impact on social inclusion among college students in Gurugram, Haryana. Surveying 240 students from 12 government colleges, findings indicate that 65 actively engage in online discussions, with 80 demonstrating moderate to high awareness of Ambedkars ideals. Statistically significant correlations reveal that higher online engagement correlates with increased awareness p 0.05 and perceived social inclusion. Variations across colleges and a notable effect of college type on perceived social inclusion highlight the influence of contextual factors. Furthermore, the intersectional analysis underscores nuanced differences based on gender, caste, and socio economic status. Dr. Kusum Lata "Online Voices, Offline Impact: Ambedkar's Ideals and Socio-Political Inclusion - A Study of Gurugram District" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64543.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/political-science/64543/online-voices-offline-impact-ambedkars-ideals-and-sociopolitical-inclusion--a-study-of-gurugram-district/dr-kusum-lata
Problems and Challenges of Agro Entreprenurship A Studyijtsrd
Noting calls for contextualizing Agro entrepreneurs problems and challenges of the agro entrepreneurs and for greater attention to the Role of entrepreneurs in agro entrepreneurship research, we conduct a systematic literature review of extent research in agriculture entrepreneurship to overcome the study objectives of complications of agro entrepreneurs through various factors, Development of agriculture products is a key factor for the overall economic growth of agro entrepreneurs Agro Entrepreneurs produces firsthand large scale employment, utilizes the labor and natural resources, This research outlines the problems of Weather and Soil Erosions, Market price fluctuation, stimulates labor cost problems, reduces concentration of Price volatility, Dependency on Intermediaries, induces Limited Bargaining Power, and Storage and Transportation Costs. This paper mainly devoted to highlight Problems and challenges faced for the sustainable of Agro Entrepreneurs in India. Vinay Prasad B "Problems and Challenges of Agro Entreprenurship - A Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64540.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64540/problems-and-challenges-of-agro-entreprenurship--a-study/vinay-prasad-b
Comparative Analysis of Total Corporate Disclosure of Selected IT Companies o...ijtsrd
Disclosure is a process through which a business enterprise communicates with external parties. A corporate disclosure is communication of financial and non financial information of the activities of a business enterprise to the interested entities. Corporate disclosure is done through publishing annual reports. So corporate disclosure through annual reports plays a vital role in the life of all the companies and provides valuable information to investors. The basic objectives of corporate disclosure is to give a true and fair view of companies to the parties related either directly or indirectly like owner, government, creditors, shareholders etc. in the companies act, provisions have been made about mandatory and voluntary disclosure. The IT sector in India is rapidly growing, the trend to invest in the IT sector is rising and employment opportunities in IT sectors are also increasing. Therefore the IT sector is expected to have fair, full and adequate disclosure of all information. Unfair and incomplete disclosure may adversely affect the entire economy. A research study on disclosure practices of IT companies could play an important role in this regard. Hence, the present research study has been done to study and review comparative analysis of total corporate disclosure of selected IT companies of India and to put forward overall findings and suggestions with a view to increase disclosure score of these companies. The researcher hopes that the present research study will be helpful to all selected Companies for improving level of corporate disclosure through annual reports as well as the government, creditors, investors, all business organizations and upcoming researcher for comparative analyses of level of corporate disclosure with special reference to selected IT companies. Dr. Vaibhavi D. Thaker "Comparative Analysis of Total Corporate Disclosure of Selected IT Companies of India" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64539.pdf Paper Url: https://www.ijtsrd.com/other-scientific-research-area/other/64539/comparative-analysis-of-total-corporate-disclosure-of-selected-it-companies-of-india/dr-vaibhavi-d-thaker
The Impact of Educational Background and Professional Training on Human Right...ijtsrd
This study investigated the impact of educational background and professional training on human rights awareness among secondary school teachers in the Marathwada region of Maharashtra, India. The key findings reveal that higher levels of education, particularly a master’s degree, and fields of study related to education, humanities, or social sciences are associated with greater human rights awareness among teachers. Additionally, both pre service teacher training and in service professional development programs focused on human rights education significantly enhance teacher’s knowledge, skills, and competencies in promoting human rights principles in their classrooms. Baig Ameer Bee Mirza Abdul Aziz | Dr. Syed Azaz Ali Amjad Ali "The Impact of Educational Background and Professional Training on Human Rights Awareness among Secondary School Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64529.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64529/the-impact-of-educational-background-and-professional-training-on-human-rights-awareness-among-secondary-school-teachers/baig-ameer-bee-mirza-abdul-aziz
A Study on the Effective Teaching Learning Process in English Curriculum at t...ijtsrd
“One Language sets you in a corridor for life. Two languages open every door along the way” Frank Smith English as a foreign language or as a second language has been ruling in India since the period of Lord Macaulay. But the question is how much we teach or learn English properly in our culture. Is there any scope to use English as a language rather than a subject How much we learn or teach English without any interference of mother language specially in the classroom teaching learning scenario in West Bengal By considering all these issues the researcher has attempted in this article to focus on the effective teaching learning process comparing to other traditional strategies in the field of English curriculum at the secondary level to investigate whether they fulfill the present teaching learning requirements or not by examining the validity of the present curriculum of English. The purpose of this study is to focus on the effectiveness of the systematic, scientific, sequential and logical transaction of the course between the teachers and the learners in the perspective of the 5Es programme that is engage, explore, explain, extend and evaluate. Sanchali Mondal | Santinath Sarkar "A Study on the Effective Teaching Learning Process in English Curriculum at the Secondary Level of West Bengal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd62412.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/62412/a-study-on-the-effective-teaching-learning-process-in-english-curriculum-at-the-secondary-level-of-west-bengal/sanchali-mondal
The Role of Mentoring and Its Influence on the Effectiveness of the Teaching ...ijtsrd
This paper reports on a study which was conducted to investigate the role of mentoring and its influence on the effectiveness of the teaching of Physics in secondary schools in the South West Region of Cameroon. The study adopted the convergent parallel mixed methods design, focusing on respondents in secondary schools in the South West Region of Cameroon. Both quantitative and qualitative data were collected, analysed separately, and the results were compared to see if the findings confirm or disconfirm each other. The quantitative analysis found that majority of the respondents 72 of Physics teachers affirmed that they had more experienced colleagues as mentors to help build their confidence, improve their teaching, and help them improve their effectiveness and efficiency in guiding learners’ achievements. Only 28 of the respondents disagreed with these statements. With majority respondents 72 agreeing with the statements, it implies that in most secondary schools, experienced Physics teachers act as mentors to build teachers’ confidence in teaching and improving students’ learning. The interview qualitative data analysis summarized how secondary school Principals use meetings with mentors and mentees to promote mentorship in the school milieu. This has helped strengthen teachers’ classroom practices in secondary schools in the South West Region of Cameroon. With the results confirming each other, the study recommends that mentoring should focus on helping teachers employ social interactions and instructional practices feedback and clarity in teaching that have direct measurable impact on students’ learning achievements. Andrew Ngeim Sumba | Frederick Ebot Ashu | Peter Agborbechem Tambi "The Role of Mentoring and Its Influence on the Effectiveness of the Teaching of Physics in Secondary Schools in the South West Region of Cameroon" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64524.pdf Paper Url: https://www.ijtsrd.com/management/management-development/64524/the-role-of-mentoring-and-its-influence-on-the-effectiveness-of-the-teaching-of-physics-in-secondary-schools-in-the-south-west-region-of-cameroon/andrew-ngeim-sumba
Design Simulation and Hardware Construction of an Arduino Microcontroller Bas...ijtsrd
This study primarily focuses on the design of a high side buck converter using an Arduino microcontroller. The converter is specifically intended for use in DC DC applications, particularly in standalone solar PV systems where the PV output voltage exceeds the load or battery voltage. To evaluate the performance of the converter, simulation experiments are conducted using Proteus Software. These simulations provide insights into the input and output voltages, currents, powers, and efficiency under different state of charge SoC conditions of a 12V,70Ah rechargeable lead acid battery. Additionally, the hardware design of the converter is implemented, and practical data is collected through operation, monitoring, and recording. By comparing the simulation results with the practical results, the efficiency and performance of the designed converter are assessed. The findings indicate that while the buck converter is suitable for practical use in standalone PV systems, its efficiency is compromised due to a lower output current. Chan Myae Aung | Dr. Ei Mon "Design Simulation and Hardware Construction of an Arduino-Microcontroller Based DC-DC High-Side Buck Converter for Standalone PV System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64518.pdf Paper Url: https://www.ijtsrd.com/engineering/mechanical-engineering/64518/design-simulation-and-hardware-construction-of-an-arduinomicrocontroller-based-dcdc-highside-buck-converter-for-standalone-pv-system/chan-myae-aung
Sustainable Energy by Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadikuijtsrd
Energy becomes sustainable if it meets the needs of the present without compromising the ability of future generations to meet their own needs. Some of the definitions of sustainable energy include the considerations of environmental aspects such as greenhouse gas emissions, social, and economic aspects such as energy poverty. Generally far more sustainable than fossil fuel are renewable energy sources such as wind, hydroelectric power, solar, and geothermal energy sources. Worthy of note is that some renewable energy projects, like the clearing of forests to produce biofuels, can cause severe environmental damage. The sustainability of nuclear power which is a low carbon source is highly debated because of concerns about radioactive waste, nuclear proliferation, and accidents. The switching from coal to natural gas has environmental benefits, including a lower climate impact, but could lead to delay in switching to more sustainable options. “Carbon capture and storage” can be built into power plants to remove the carbon dioxide CO2 emissions, but this technology is expensive and has rarely been implemented. Leading non renewable energy sources around the world is fossil fuels, coal, petroleum, and natural gas. Nuclear energy is usually considered another non renewable energy source, although nuclear energy itself is a renewable energy source, but the material used in nuclear power plants is not. The paper addresses the issue of sustainable energy, its attendant benefits to the future generation, and humanity in general. Paul A. Adekunte | Matthew N. O. Sadiku | Janet O. Sadiku "Sustainable Energy" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64534.pdf Paper Url: https://www.ijtsrd.com/engineering/electrical-engineering/64534/sustainable-energy/paul-a-adekunte
Concepts for Sudan Survey Act Implementations Executive Regulations and Stand...ijtsrd
This paper aims to outline the executive regulations, survey standards, and specifications required for the implementation of the Sudan Survey Act, and for regulating and organizing all surveying work activities in Sudan. The act has been discussed for more than 5 years. The Land Survey Act was initiated by the Sudan Survey Authority and all official legislations were headed by the Sudan Ministry of Justice till it was issued in 2022. The paper presents conceptual guidelines to be used for the Survey Act implementation and to regulate the survey work practice, standardizing the field surveys, processing, quality control, procedures, and the processes related to survey work carried out by the stakeholders and relevant authorities in Sudan. The conceptual guidelines are meant to improve the quality and harmonization of geospatial data and to aid decision making processes as well as geospatial information systems. The established comprehensive executive regulations will govern and regulate the implementation of the Sudan Survey Geomatics Act in all surveying and mapping practices undertaken by the Sudan Survey Authority SSA and state local survey departments for public or private sector organizations. The targeted standards and specifications include the reference frame, projection, coordinate systems, and the guidelines and specifications that must be followed in the field of survey work, processes, and mapping products. In the last few decades, there has been a growing awareness of the importance of geomatics activities and measurements on the Earths surface in space and time, together with observing and mapping the changes. In such cases, data must be captured promptly, standardized, and obtained with more accuracy and specified in much detail. The paper will also highlight the current situation in Sudan, the degree to which survey standards are used, the problems encountered, and the errors that arise from not using the standards and survey specifications. Kamal A. A. Sami "Concepts for Sudan Survey Act Implementations - Executive Regulations and Standards" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63484.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63484/concepts-for-sudan-survey-act-implementations--executive-regulations-and-standards/kamal-a-a-sami
Towards the Implementation of the Sudan Interpolated Geoid Model Khartoum Sta...ijtsrd
The discussions between ellipsoid and geoid have invoked many researchers during the recent decades, especially during the GNSS technology era, which had witnessed a great deal of development but still geoid undulation requires more investigations. To figure out a solution for Sudans local geoid, this research has tried to intake the possibility of determining the geoid model by following two approaches, gravimetric and geometrical geoid model determination, by making use of GNSS leveling benchmarks at Khartoum state. The Benchmarks are well distributed in the study area, in which, the horizontal coordinates and the height above the ellipsoid have been observed by GNSS while orthometric heights were carried out using precise leveling. The Global Geopotential Model GGM represented in EGM2008 has been exploited to figure out the geoid undulation at the benchmarks in the study area. This is followed by a fitting process, that has been done to suit the geoid undulation data which has been computed using GNSS leveling data and geoid undulation inspired by the EGM2008. Two geoid surfaces were created after the fitting process to ensure that they are identical and both of them could be counted for getting the same geoid undulation with an acceptable accuracy. In this respect, statistical operation played an important role in ensuring the consistency and integrity of the model by applying cross validation techniques splitting the data into training and testing datasets for building the geoid model and testing its eligibility. The geometrical solution for geoid undulation computation has been utilized by applying straightforward equations that facilitate the calculation of the geoid undulation directly through applying statistical techniques for the GNSS leveling data of the study area to get the common equation parameters values that could be utilized to calculate geoid undulation of any position in the study area within the claimed accuracy. Both systems were checked and proved eligible to be used within the study area with acceptable accuracy which may contribute to solving the geoid undulation problem in the Khartoum area, and be further generalized to determine the geoid model over the entire country, and this could be considered in the future, for regional and continental geoid model. Ahmed M. A. Mohammed. | Kamal A. A. Sami "Towards the Implementation of the Sudan Interpolated Geoid Model (Khartoum State Case Study)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63483.pdf Paper Url: https://www.ijtsrd.com/engineering/civil-engineering/63483/towards-the-implementation-of-the-sudan-interpolated-geoid-model-khartoum-state-case-study/ahmed-m-a-mohammed
Activating Geospatial Information for Sudans Sustainable Investment Mapijtsrd
Sudan is witnessing an acceleration in the processes of development and transformation in the performance of government institutions to raise the productivity and investment efficiency of the government sector. The development plans and investment opportunities have focused on achieving national goals in various sectors. This paper aims to illuminate the path to the future and provide geospatial data and information to develop the investment climate and environment for all sized businesses, and to bridge the development gap between the Sudan states. The Sudan Survey Authority SSA is the main advisor to the Sudan Government in conducting surveying, mappings, designing, and developing systems related to geospatial data and information. In recent years, SSA made a strategic partnership with the Ministry of Investment to activate Geospatial Information for Sudans Sustainable Investment and in particular, for the preparation and implementation of the Sudan investment map, based on the directives and objectives of the Ministry of Investment MI in Sudan. This paper comes within the framework of activating the efforts of the Ministry of Investment to develop technical investment services by applying techniques adopted by the Ministry and its strategic partners for advancing investment processes in the country. Kamal A. A. Sami "Activating Geospatial Information for Sudan's Sustainable Investment Map" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63482.pdf Paper Url: https://www.ijtsrd.com/engineering/information-technology/63482/activating-geospatial-information-for-sudans-sustainable-investment-map/kamal-a-a-sami
Educational Unity Embracing Diversity for a Stronger Societyijtsrd
In a rapidly changing global landscape, the importance of education as a unifying force cannot be overstated. This paper explores the crucial role of educational unity in fostering a stronger and more inclusive society through the embrace of diversity. By examining the benefits of diverse learning environments, the paper aims to highlight the positive impact on societal strength. The discussion encompasses various dimensions, from curriculum design to classroom dynamics, and emphasizes the need for educational institutions to become catalysts for unity in diversity. It highlights the need for a paradigm shift in educational policies, curricula, and pedagogical approaches to ensure that they are reflective of the diverse fabric of society. This paper also addresses the challenges associated with implementing inclusive educational practices and offers practical strategies for overcoming barriers. It advocates for collaborative efforts between educational institutions, policymakers, and communities to create a supportive ecosystem that promotes diversity and unity. Mr. Amit Adhikari | Madhumita Teli | Gopal Adhikari "Educational Unity: Embracing Diversity for a Stronger Society" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64525.pdf Paper Url: https://www.ijtsrd.com/humanities-and-the-arts/education/64525/educational-unity-embracing-diversity-for-a-stronger-society/mr-amit-adhikari
Integration of Indian Indigenous Knowledge System in Management Prospects and...ijtsrd
The diversity of indigenous knowledge systems in India is vast and can vary significantly between different communities and regions. Preserving and respecting these knowledge systems is crucial for maintaining cultural heritage, promoting sustainable practices, and fostering cross cultural understanding. In this paper, an overview of the prospects and challenges associated with incorporating Indian indigenous knowledge into management is explored. It is found that IIKS helps in management in many areas like sustainable development, tourism, food security, natural resource management, cultural preservation and innovation, etc. However, IIKS integration with management faces some challenges in the form of a lack of documentation, cultural sensitivity, language barriers legal framework, etc. Savita Lathwal "Integration of Indian Indigenous Knowledge System in Management: Prospects and Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63500.pdf Paper Url: https://www.ijtsrd.com/management/accounting-and-finance/63500/integration-of-indian-indigenous-knowledge-system-in-management-prospects-and-challenges/savita-lathwal
DeepMask Transforming Face Mask Identification for Better Pandemic Control in...ijtsrd
The COVID 19 pandemic has highlighted the crucial need of preventive measures, with widespread use of face masks being a key method for slowing the viruss spread. This research investigates face mask identification using deep learning as a technological solution to be reducing the risk of coronavirus transmission. The proposed method uses state of the art convolutional neural networks CNNs and transfer learning to automatically recognize persons who are not wearing masks in a variety of circumstances. We discuss how this strategy improves public health and safety by providing an efficient manner of enforcing mask wearing standards. The report also discusses the obstacles, ethical concerns, and prospective applications of face mask detection systems in the ongoing fight against the pandemic. Dilip Kumar Sharma | Aaditya Yadav "DeepMask: Transforming Face Mask Identification for Better Pandemic Control in the COVID-19 Era" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd64522.pdf Paper Url: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/64522/deepmask-transforming-face-mask-identification-for-better-pandemic-control-in-the-covid19-era/dilip-kumar-sharma
Streamlining Data Collection eCRF Design and Machine Learningijtsrd
Efficient and accurate data collection is paramount in clinical trials, and the design of Electronic Case Report Forms eCRFs plays a pivotal role in streamlining this process. This paper explores the integration of machine learning techniques in the design and implementation of eCRFs to enhance data collection efficiency. We delve into the synergies between eCRF design principles and machine learning algorithms, aiming to optimize data quality, reduce errors, and expedite the overall data collection process. The application of machine learning in eCRF design brings forth innovative approaches to data validation, anomaly detection, and real time adaptability. This paper discusses the benefits, challenges, and future prospects of leveraging machine learning in eCRF design for streamlined and advanced data collection in clinical trials. Dhanalakshmi D | Vijaya Lakshmi Kannareddy "Streamlining Data Collection: eCRF Design and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-1 , February 2024, URL: https://www.ijtsrd.com/papers/ijtsrd63515.pdf Paper Url: https://www.ijtsrd.com/biological-science/biotechnology/63515/streamlining-data-collection-ecrf-design-and-machine-learning/dhanalakshmi-d
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
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It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
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Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
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II. LITERATURE WORK
By using the capabilities of Natural language
processing (NLP) to analyze the sentiment that is
being expressed in the specific data, the notion of
opinion mining or sentiment analysis has been
employed and modified for diverse studies throughout
time. Previous studies that have shed light on this
topic are discussed below.
In the paper[1], the BERT model is used to do
Sentiment Analysis on Twitter data. Tweets were
geotagged in order to classify the data utilized in this
work. The BERT model for emotion categorization
was used to train the data, and the SVM classifier was
used to assess the model's effectiveness. On the
whole, the acquired data was accurate to within 4%.
Paper [2] presents an analytical framework for impact
of COVID-19 on the stock market based on tweets
during the outbreak. Supervised learning was used to
train this model, which achieved an accuracy of 86.24
percent. The studies were conducted after the
Coronavirus epidemic to aid businesses in forecasting
stock prices, identifying new marketing opportunities,
and monitoring their own growth. In paper [3], we
analyze what people were tweeting about most during
and after the first outbreak of the COVID-19
pandemic. For topic extraction, we used Latent
Dirichlet Allocation (LDA), and for sentiment
analysis, we relied on a Lexicon-based strategy. This
report does a good job of summing up the concerns of
different groups during the early stages of the
epidemic. Using a dataset of 600,000 English-
language tweets, the model was trained using 80% of
the data and then tested using 20% of the data. The
article used sentiment analysis to illustrate people's
thoughts on the most discussed issues.
This paper [4] examines tweets from across all of
India's states during the months of November 2019
and May 2022. In this article, we successfully used
sentiment analysis to the gathered information and
found that, on the whole, Indians had an optimistic
outlook on life.
There was a correlation between the number of
confirmed cases of COVID19 in a given state and the
number of tweets sent from that state. The research
[5] provides a comprehensive analysis of the tone of
all tweets related to COVID-19. In this case, we
evaluated the tone of the tweets using Logistic
Regression, VADER sentiment analysis, and BERT
sentiment analysis. In order to analyze public opinion
on the issue of Coronavirus, the authors of paper [6]
combine data from two sources: the textual tweets
posted in April 2020 from six nations and the tweets
of top 10 politicians. In the end, the report presents
findings that shed light on the similarities and
variances in public opinion among nations. The
results showed that across all six nations, respondents
felt the most "trust," "fear," and "anticipation."
Sentiment analysis utilizing word weighting TF-IDF
and Logistic Regression was performed on the
Twitter data from 30th April 2020 in article [7]. This
algorithm successfully classified the sentiment of the
tweets with an accuracy of 94.71%.
Our understanding of the prior studies in this area was
much enhanced by this literature study. Our project's
trajectory is now clearer thanks to this.
III. SENTIMENT ANALYSIS
An application of Natural Language Processing
(NLP), sentiment analysis classifies data and texts to
reveal how people feel about a topic [8]. This helps in
understanding the author's intentions and point of
view. This technique uses a scoring system that
shows the true meaning and viewpoint of the text. We
can more quickly identify positive, bad, and neutral
aspects of the material by using these evaluations.
Businesses regularly use opinion mining (or
"Emotion AI") and sentiment analysis (or "sentiment
analysis") to get insight into how customers and the
wider public feel about a brand or product.
To gauge public opinion about COVID vaccinations,
we use Sentiment Analysis to data gathered from
Twitter after the second wave of Coronavirus. The
study's findings may provide light on the public's
thoughts and feelings towards COVID-19 vaccines.
There are two main phases to any sentiment analysis:
1. Prioritizing, sanitizing, and selecting features
from datasets
2. Applying Sentiment Analysis to the Data
IV. DATASET DESCRIPTION
The project began off with information collection and
classification. For this study, we analyzed data from
the 'Covid-19 All Vaccine Tweets' collection. The
data, which covers the period from December 2020 to
August 2021 and consists of 80,418 tweets, was
acquired from kaggle.com [9]. Table 1 lists the
characteristics and provides explanations for each.
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Table 1: Attributes of the dataset and their description
ATTRIBUTES DESCRIPTION
id This gives the id of the tweet
user_name User name of the person who has tweeted
user_location The location of the person who has sent the tweet
user_description The Twitter bio of the person writing the tweet
user_created When the Twitter account of the user was created
user_followers Number of followers of the person sending the tweet
user_friends Number of friends of the person sending the tweet
user_verified Binary value specifying whether the user is verified on Twitter or not
date Date and time when the tweet was sent
text The text in the tweet as it is
hashtags Specifies all the hashtags that were used in the tweet
source Gives information about the source(device or application) from which the tweet was sent
retweets Number of times the tweet was retweeted
favourites Number of people who have marked the tweet as a ‘favourite’
is_retweet Tells us if the tweet is a retweet or a new one
Following this, the tweets in the dataset were cleaned up by removing things like mentions, hashtags, retweet
information, and links. Time stamps for tweets were also eliminated since they were deemed unnecessary. Some
of the most salient characteristics from the aforementioned list are chosen for exploratory research.
V. METHODOLOGY
This section explains in depth how Sentiment Analysis was carried out on the selected dataset.
Gathering information that may be used in the analysis was the first stage. The same was discussed at length in
the preceding paragraph. The dataset contains clean, pre-processed data. Eighty three hundred and six records
survived after duplicate columns were removed from the dataset. The tweets were then cleaned up by removing
any traces of mentions, hashtags, retweets, links, etc. We also scrubbed the data for tweet timestamps. Then, a
subset of the aforementioned traits was chosen since it was more relevant to the data analysis being conducted. A
few key graphs were displayed after a graphical study of the data was performed.
The number of tweets sent from each device type is displayed in Fig. 1. The majority of tweets were sent from
Android devices, followed by the Twitter Web App, and then the Cowin Vaccination Availability platform, as
seen in the provided scatter plot.
Figure 1: Plot showing the source of the tweets posted
Figure 2 displays the distribution of tweets between verified and unverified accounts. The narrative reveals that
about 10% of tweets came from verified accounts, while the remaining 90% came from unverified ones.
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Figure 2: Plot showing the number of tweets sent from verified or unverified accounts
The most popular tweets about COVID-19 vaccinations were identified by taking the top 10 most retweeted
tweets from the dataset. They look like Fig. 3 down below.
Figure 3: Top 10 most retweeted tweets related to COVID-19 vaccine.
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The top 20 accounts based on the frequency of the tweets were found out. They are as shown in Fig. 4 below.
Figure 4: Top 20 accounts based on the frequency of the tweets
The information was divided into three groups, one for each polarity value. Tweets with polarity values between
-1 and -0.01 were classified as negative. There are three types of tweets: positive (1), negative (-1) and neutral
(0). Tweets with polarity values between -0.01 and 0.01 were labeled as "Neutral," while those with polarity
values between 0.01 and 1 were labeled as "Positive." The number of tweets that fall into each of these three
categories is shown in Fig. 5.
Figure 5:Tweet count given as positive, negative or neutral class
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Figure 6 shows the CDF of tweet sentiments and the distribution of tweet sentiments throughout the sample.
Distribution of Sentiments Across Our Tweets
CDF of Sentiments Across Our Tweets
Figure 6: Distribution and CDF of Sentiments across tweets in the dataset
Next, we identified the most frequently used terms in both the most positive and negative tweets in the total
dataset and created word clouds for them. Fig. 8 below illustrates this point.
The chart below shows the public's overwhelmingly favorable reaction to the COVID-19 vaccinations, with the
most prevalent phrases being "good," "thank," "effective," "vaccinated," "great," "happy," "safe," etc.
Emergency, forced, alone, Canada, halt, second, death, India, Ontario, etc. were other frequent terms in the
unfavorable tweets.
Figure 7: Word Clouds for the common words among the most positive and most negative tweets
To go further, we plotted word clouds from tweets about a select number of nations and places. Figures 8 and 9
and Figure 10 depict them below.
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Figure 8: Most common words in tweets related to India
Figure 9: Most common words in tweets related to USA
Figure 10: Most common words in tweets related to Mumbai
Due to the limited vaccination options in India, we created a word cloud from tweets about Covaxin and
Covishield. Fig. 11 displays this.
Figure 11: Word cloud for the tweets Covishield and Covaxin
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The data was then processed using some sophisticated methods to generate the color-coded word clouds for the
divided tweets. The information was once again scrubbed. The tweets were filtered to remove any grammatical
or spelling errors or nonsense. After that, the whole Twitter data was classified into positive, negative, and
neutral categories, and corresponding cloud words were formed for each. That's what Fig. 12 shows.
Figure 12: Colour-coded word clouds for all the tweets
Similarly, the colour-coded word clouds for the Covishield and Covaxin were also plotted which is shown in
Fig. 13 below.
Figure 13: Colour-coded word clouds for the Covishield and Covaxin
A. Polarity
A word's polarity is the degree to which it expresses a negative, neutral, or positive emotion. Words with a
positive polarity have a value of 1, whereas neutral words have no polarity and negative words have a value of -
1. The polarity of a tweet is calculated by taking the mean of all the words in it, which is a float value between -1
and +1. Polarity of a tweet is a matrix that breaks down a tweet's emotional tone into positive, negative, and
neutral categories.
B. Subjectivity
The ratio of subjective to objective details in a tweet or paragraph depends on the
speaker. The degree to which a writing is subjective rises as more private details are included and falls as more
objective data is presented. It's a proxy for the author's degree of involvement in the tweet or other source
content.
A small subset of the dataset's generalizations about vaccination was then chosen for testing of polarity and
subjectivity in terms of sentiment. In Figures 4 and 5, we see the polarity and subjectivity ratings.
Figure 14: Polarity score of the tweets
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Figure 15: Subjectivity score of the tweets
The following is a flowchart depicting the research procedure that was used.
Figure 16: A flowchart of the methodology followed for implementation of this project
VI. RESULTS AND DISCUSSIONS
In this study, 16,05,152 tweets and retweets were
analysed for attitude about immunization in India.
After being cleaned, pre-processed, and having
duplicates removed, the data utilized in the research
was ready for analysis. The tweets had their
timestamps, mentions, hashtags, retweets, and links
deleted. Word clouds of varying permutations were
extracted while also plotting crucial graphs like
emotion labels graphs and distribution graphs, among
others, to get the gist of the data. Additionally, a few
general comments about vaccination were chosen and
examined for polarity and subjectivity to determine
how they were received. Data analysis shows that the
majority of Indians have a favourable opinion about
vaccination, but that there is still a strong negative
attitude towards the practice in the country.
VII. CONCLUSION AND FUTURE SCOPE
The public has been affected in a variety of ways by
the coronavirus, and this sort of study may aid
government and other research organizations in
comprehending public sentiment and filling in
knowledge gaps. Twitter data analysis is crucial since
it is a place where many individuals express their
honest, sometimes controversial, opinions. With the
help of Natural Language Processing (NLP) methods
like subjectivity and polarity, the study analyses
millions of public views expressed via tweets on the
Twitter network and provides us with the necessary
analysis as outputs in the form of graphs and tables.
This study's findings highlight the need for increased
vaccination awareness and provide new insight into
the factors that make some individuals feel uneasy
about being vaccinated.
Since it is crucial to grasp the public's mood in a
variety of scenarios, this research has significant
future potential. Sentiment analysis may be conducted
again to examine public opinion on the third wave,
public opinion on immunization delay in India, and
similar subjects. There is a wealth of relevant data at
our disposal, which we may decipher and analyse for
use as a springboard for future action. Any piece of
private information may be utilized as a dataset to
help analyse the tone of a tweet or other piece of data.
In today's lightning-fast, data-powered world, having
a matrix to better comprehend the reasoning behind
opinions on how to use data is critical.