This document discusses analyzing sentiment from tweets about the 2019 Pulwama attack in India. It proposes collecting tweets using Apache Nifi, storing them in HDFS, preprocessing the data with Hive, and analyzing sentiment using Tableau. The methodology involves fetching tweets via Twitter API, uploading to HDFS with Nifi, structuring the unstructured JSON data with Hive, removing null values with preprocessing, and visualizing sentiment analysis results in Tableau. Tools like Hadoop, MapReduce, HDFS, Hive, Nifi and Tableau are discussed for handling big Twitter data and performing sentiment analysis in order to understand public opinions expressed on social media.
Detailed Investigation of Text Classification and Clustering of Twitter Data ...ijtsrd
As of late there has been a growth in data. This paper presents a methodology to investigate the text classification of data gathered from twitter. In this study sentiment analysis has been done on online comment data giving us picture of how to discover the demands of a people. Ziya Fatima | Er. Vandana "Detailed Investigation of Text Classification and Clustering of Twitter Data for Business Analytics" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38527.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/38527/detailed-investigation-of-text-classification-and-clustering-of-twitter-data-for-business-analytics/ziya-fatima
Detailed Investigation of Text Classification and Clustering of Twitter Data ...ijtsrd
As of late there has been a growth in data. This paper presents a methodology to investigate the text classification of data gathered from twitter. In this study sentiment analysis has been done on online comment data giving us picture of how to discover the demands of a people. Ziya Fatima | Er. Vandana "Detailed Investigation of Text Classification and Clustering of Twitter Data for Business Analytics" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-2 , February 2021, URL: https://www.ijtsrd.com/papers/ijtsrd38527.pdf Paper Url: https://www.ijtsrd.com/engineering/computer-engineering/38527/detailed-investigation-of-text-classification-and-clustering-of-twitter-data-for-business-analytics/ziya-fatima
Methods for Sentiment Analysis: A Literature Studyvivatechijri
Sentiment analysis is a trending topic, as everyone has an opinion on everything. The systematic
study of these opinions can lead to information which can prove to be valuable for many companies and
industries in future. A huge number of users are online, and they share their opinions and comments regularly,
this information can be mined and used efficiently. Various companies can review their own product using
sentiment analysis and make the necessary changes in future. The data is huge and thus it requires efficient
processing to collect this data and analyze it to produce required result.
In this paper, we will discuss the various methods used for sentiment analysis. It also covers various techniques
used for sentiment analysis such as lexicon based approach, SVM [10], Convolution neural network,
morphological sentence pattern model [1] and IML algorithm. This paper shows studies on various data sets
such as Twitter API, Weibo, movie review, IMDb, Chinese micro-blog database [9] and more. The paper shows
various accuracy results obtained by all the systems.
A real-time big data sentiment analysis for iraqi tweets using spark streamingjournalBEEI
The scale of data streaming in social networks, such as Twitter, is increasing exponentially. Twitter is one of the most important and suitable big data sources for machine learning research in terms of analysis, prediction, extract knowledge, and opinions. People use Twitter platform daily to express their opinion which is a fundamental fact that influence their behaviors. In recent years, the flow of Iraqi dialect has been increased, especially on the Twitter platform. Sentiment analysis for different dialects and opinion mining has become a hot topic in data science researches. In this paper, we will attempt to develop a real-time analytic model for sentiment analysis and opinion mining to Iraqi tweets using spark streaming, also create a dataset for researcher in this field. The Twitter handle Bassam AlRawi is the case study here. The new method is more suitable in the current day machine learning applications and fast online prediction.
A Hybrid Approach for Supervised Twitter Sentiment Classification ....................................................1
K. Revathy and Dr. B. Sathiyabhama
A Survey of Dynamic Duty Cycle Scheduling Scheme at Media Access Control Layer for Energy
Conservation .....................................................................................................................................1
Prof. M. V. Nimbalkar and Sampada Khandare
A Survey on Privacy Preserving Data Mining Techniques ....................................................................1
A. K. Ilavarasi, B. Sathiyabhama and S. Poorani
An Ontology Based System for Predicting Disease using SWRL Rules ...................................................1
Mythili Thirugnanam, Tamizharasi Thirugnanam and R. Mangayarkarasi
Performance Evaluation of Web Services in C#, JAVA, and PHP ..........................................................1
Dr. S. Sagayaraj and M. Santhosh Kumar
Semi-Automated Polyhouse Cultivation Using LabVIEW......................................................................1
Prathiba Jonnala and Sivaji Satrasupalli
Performance of Biometric Palm Print Personal Identification Security System Using Ordinal Measures 1
V. K. Narendira Kumar and Dr. B. Srinivasan
MIMO System for Next Generation Wireless Communication..............................................................1
Sharif, Mohammad Emdadul Haq and Md. Arif Rana
The project is to ask college related queries and get the responses through a chatbot an Artificial Conversational Entity. This System is a web application which provides answer to the query of the student. Students just have to query through the bot which is used for chatting. Students can chat using any format there is no specific format the user has to follow. This system helps the student to be updated about the college activities.
Sentimental Emotion Analysis using Python and Machine LearningYogeshIJTSRD
Sentiment analysis is used in opinion mining. It helps businesses understand the customers’ reviews with a particular product by analyzing their emotional from the product reviews they post, the online recommendations they make, their survey responses and other forms of social media text. Businesses can get feedback on how happy or sad the customer is, and use this insight to gain a competitive edge. In this article, we explore how to conduct sentiment analysis on a piece of text using some machine learning techniques. Python happens to be one of the best programming language, when it comes to machine learning as it is easy to learn, is open source, and is effective in catering to machine learning requirements like processing big datasets and performing mathematical computations. Natural Language ToolKit NLTK is one of the popular packages in Python that can use for in sentiment analysis. Mohit Chaudhari "Sentimental Emotion Analysis using Python and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41198.pdf Paper URL: https://www.ijtsrd.comengineering/computer-engineering/41198/sentimental-emotion-analysis-using-python-and-machine-learning/mohit-chaudhari
Keyphrase Extraction using Neighborhood KnowledgeIJMTST Journal
This paper focus on keyphrase extraction for news articles because news article is one of the popular document genres on the web and most news articles have no author-assigned keyphrases. Existing methods for single document keyphrase extraction usually make use of only the information contained in the specified document. This paper proposes to use a small number of nearest neighbor documents to provide more knowledge to improve single document keyphrase extraction. Experimental results demonstrate the good effectiveness and robustness of our proposed approach. According to experiments conducted on several documents and keyphrases we consider top 10 keyphrases are most suitable keyphrases.
Methods for Sentiment Analysis: A Literature Studyvivatechijri
Sentiment analysis is a trending topic, as everyone has an opinion on everything. The systematic
study of these opinions can lead to information which can prove to be valuable for many companies and
industries in future. A huge number of users are online, and they share their opinions and comments regularly,
this information can be mined and used efficiently. Various companies can review their own product using
sentiment analysis and make the necessary changes in future. The data is huge and thus it requires efficient
processing to collect this data and analyze it to produce required result.
In this paper, we will discuss the various methods used for sentiment analysis. It also covers various techniques
used for sentiment analysis such as lexicon based approach, SVM [10], Convolution neural network,
morphological sentence pattern model [1] and IML algorithm. This paper shows studies on various data sets
such as Twitter API, Weibo, movie review, IMDb, Chinese micro-blog database [9] and more. The paper shows
various accuracy results obtained by all the systems.
A real-time big data sentiment analysis for iraqi tweets using spark streamingjournalBEEI
The scale of data streaming in social networks, such as Twitter, is increasing exponentially. Twitter is one of the most important and suitable big data sources for machine learning research in terms of analysis, prediction, extract knowledge, and opinions. People use Twitter platform daily to express their opinion which is a fundamental fact that influence their behaviors. In recent years, the flow of Iraqi dialect has been increased, especially on the Twitter platform. Sentiment analysis for different dialects and opinion mining has become a hot topic in data science researches. In this paper, we will attempt to develop a real-time analytic model for sentiment analysis and opinion mining to Iraqi tweets using spark streaming, also create a dataset for researcher in this field. The Twitter handle Bassam AlRawi is the case study here. The new method is more suitable in the current day machine learning applications and fast online prediction.
A Hybrid Approach for Supervised Twitter Sentiment Classification ....................................................1
K. Revathy and Dr. B. Sathiyabhama
A Survey of Dynamic Duty Cycle Scheduling Scheme at Media Access Control Layer for Energy
Conservation .....................................................................................................................................1
Prof. M. V. Nimbalkar and Sampada Khandare
A Survey on Privacy Preserving Data Mining Techniques ....................................................................1
A. K. Ilavarasi, B. Sathiyabhama and S. Poorani
An Ontology Based System for Predicting Disease using SWRL Rules ...................................................1
Mythili Thirugnanam, Tamizharasi Thirugnanam and R. Mangayarkarasi
Performance Evaluation of Web Services in C#, JAVA, and PHP ..........................................................1
Dr. S. Sagayaraj and M. Santhosh Kumar
Semi-Automated Polyhouse Cultivation Using LabVIEW......................................................................1
Prathiba Jonnala and Sivaji Satrasupalli
Performance of Biometric Palm Print Personal Identification Security System Using Ordinal Measures 1
V. K. Narendira Kumar and Dr. B. Srinivasan
MIMO System for Next Generation Wireless Communication..............................................................1
Sharif, Mohammad Emdadul Haq and Md. Arif Rana
The project is to ask college related queries and get the responses through a chatbot an Artificial Conversational Entity. This System is a web application which provides answer to the query of the student. Students just have to query through the bot which is used for chatting. Students can chat using any format there is no specific format the user has to follow. This system helps the student to be updated about the college activities.
Sentimental Emotion Analysis using Python and Machine LearningYogeshIJTSRD
Sentiment analysis is used in opinion mining. It helps businesses understand the customers’ reviews with a particular product by analyzing their emotional from the product reviews they post, the online recommendations they make, their survey responses and other forms of social media text. Businesses can get feedback on how happy or sad the customer is, and use this insight to gain a competitive edge. In this article, we explore how to conduct sentiment analysis on a piece of text using some machine learning techniques. Python happens to be one of the best programming language, when it comes to machine learning as it is easy to learn, is open source, and is effective in catering to machine learning requirements like processing big datasets and performing mathematical computations. Natural Language ToolKit NLTK is one of the popular packages in Python that can use for in sentiment analysis. Mohit Chaudhari "Sentimental Emotion Analysis using Python and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41198.pdf Paper URL: https://www.ijtsrd.comengineering/computer-engineering/41198/sentimental-emotion-analysis-using-python-and-machine-learning/mohit-chaudhari
Keyphrase Extraction using Neighborhood KnowledgeIJMTST Journal
This paper focus on keyphrase extraction for news articles because news article is one of the popular document genres on the web and most news articles have no author-assigned keyphrases. Existing methods for single document keyphrase extraction usually make use of only the information contained in the specified document. This paper proposes to use a small number of nearest neighbor documents to provide more knowledge to improve single document keyphrase extraction. Experimental results demonstrate the good effectiveness and robustness of our proposed approach. According to experiments conducted on several documents and keyphrases we consider top 10 keyphrases are most suitable keyphrases.
Twitter word frequency count using hadoop components 150331221753pradip patel
Abstract- Analysis of twitter data can be very useful for marketing as well as for promotion strategies. This paper
implements word frequency count for 1.5+ million twitters dataset .The hadoop components such as Apache pig and
MapReduce framework are used for parallel execution of the data. This parallel execution makes the implementation
time-effective and feasible to execute on a single system
Twitter word frequency count using hadoop components 150331221753pradip patel
Analysis of twitter data can be very useful for marketing as well as for promotion strategies. This paper implements word frequency count for 1.5+ million twitters dataset .The hadoop components such as Apache pig and MapReduce framework are used for parallel execution of the data. This parallel execution makes the implementation time-effective and feasible to execute on a single system.
Design Document written partially for an assignment as a graduate student at the University of Southern California for the Techniques in Data Visualization course I took with wireframes used in the creation for an actual web application.
https://www.youtube.com/watch?v=nvlHJgRE3pU
Won ITAC Graduation Projects Competition, ITAC ID: GP2015.R10.75
A web application that analyze big volumes of product reviews, social networks posts and tweets related to a given product. Then, present these results of this big data analytical job in a user friendly, understandable, and easily interpreted manner that can be used by different customers for different purposes.
Technologies used:
1- Hadoop
2- Hadoop Streaming
3- R Statistical
4- PHP
5- Google Charts API
A Review on Software Mining: Current Trends and MethodologiesIJERA Editor
With the evolution of Software Mining, it has enabled to play a crucial role in the day to day activities .By empowering the software with the data mining methods it aids to all the software developers and the managers at all the managerial levels to use it as a tool so that the relative software engineering data (in the form of code, design documents, bug reports) to visualize the project‟s status of evolution and progress. To add on, further all the mining methods and algorithms help to device the models to develop any fault prone real time system for the real world more prior to the testing phase or the evolution phase. Also , in this review paper it will highlight the different methodologies for software mining along with its extension as a tool for fault tolerance and as well as a bibliography with the special prominence on mining the software engineering information.
Similar to IRJET- Opinion Mining on Pulwama Attack (20)
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
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Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.