A Deep Multimodal Learning Approach to Perceive Basic Needs of Humans From Instagram Profile.pdf
•
0 likes•2 views
https://okokprojects.com/ IEEE PROJECTS 2023-2024 TITLE LIST WhatsApp : +91-8144199666 From Our Title List the Cost will be, Mail Us: okokprojects@gmail.com Website: : https://www.okokprojects.com : http://www.ieeeproject.net Support Including Packages ======================= * Complete Source Code * Complete Documentation * Complete Presentation Slides * Flow Diagram * Database File * Screenshots * Execution Procedure * Video Tutorials * Supporting Softwares Support Specialization ======================= * 24/7 Support * Ticketing System * Voice Conference * Video On Demand * Remote Connectivity * Document Customization * Live Chat Support
Report
Share
Report
Share
Download to read offline
Recommended
G1803024452
This document discusses analyzing human personality characteristics from social media profiles using machine learning techniques. It collects over 3,000 profile summaries from LinkedIn using web scraping. It then uses the WordNet lexical database to form word clusters for extroversion and introversion characteristics. The k-nearest neighbors algorithm is used to classify profiles as extrovert, introvert, or ambivert based on the words in their summaries. The goal is to analyze users' profiles and provide guidance to write profiles that include a balance of introvert and extrovert traits classified as ambivert, which tends to be viewed more positively. Accuracy results from the classification approach are promising but not discussed in detail.
Social Networking Facebook My Space
The document summarizes a research study that analyzed differences in how older users and teenagers use social networking sites like MySpace. It found that teenagers had larger friend networks focused on their age/interest groups, while older users' networks were more diverse. The study effectively chose the popular MySpace platform and clearly outlined its objective to compare age groups. However, the analysis relied on self-reported profile data, which may not be accurate, and the choice to examine users age 60+ limited useful comparisons as very few in that age group use MySpace.
User Personality Prediction on Facebook Social Media using Machine Learning
In recent years, Social network use is increasingly build up. The various statistics are split widely through social media Such as Facebook, Twitter. Data about the person and what they communicate through the status updates are important for research in human personality. This paper intends to scrutinize the forecasting of personality traits of Facebook users bases on machine learning and part of the Big ve model this experiment uses my personality data set of Facebook users are used for linguistic factors respective to personality correlation. We used the Data Prepossessing concept of data mining after that feature Extraction. Next, we will work on feature selection. The Personality Prediction system built in the XGboosting classi cation model. Poonam L Patil | Dr. S. R. Jadhao "User Personality Prediction on Facebook Social Media using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33414.pdf Paper Url: https://www.ijtsrd.com/computer-science/data-miining/33414/user-personality-prediction-on-facebook-social-media-using-machine-learning/poonam-l-patil
F017433947
This document summarizes a research paper that proposes using a logistic regression classifier trained with stochastic gradient descent to predict Twitter users' personalities from their tweets. It begins with an abstract of the paper and an introduction on personality prediction from social media. It then provides more detail on the anatomy of the research, including defining personality prediction from Twitter, its applications, and the general process of using machine learning for the task. Next, it reviews several previous studies on personality prediction from Twitter and social networks, noting their approaches, findings and limitations. It identifies remaining research gaps, such as the need for improved linguistic analysis of tweets and more robust/scalable predictive models. Finally, it proposes using a logistic regression classifier as the personality prediction model to address
A Baseline Based Deep Learning Approach of Live Tweets
In this scenario social media plays a vital role in influencing the life of people. Twitter , Facebook, Instagram etc are the major social media platforms . They act as a platform for users to raise their opinions on things and events around them. Twitter is one such micro blogging site that allows the user to tweet 6000 tweets per day each of 280 characters long. Data analyst rely on this data to reach conclusion on the events happening around and also to rate a product. But due to massive volume of reviews the analysts find it difficult to go through them and reach at conclusions. In order to solve this problem we adopt the method of sentiment analysis. Sentiment analysis is an approach to classify the sentiment of user reviews, documents etc in terms of positive good , negative bad , neutral surprise . I suggest an enhanced twitter sentiment analysis that retrieves data based on a baseline in a particular pre defined time span and performs sentiment analysis using Textblob . This scheme differs from the traditional and existing one which performs sentiment analysis on pre saved data by performing sentiment analysis on real time data fetched via Twitter API . Thereby providing a much recent and relevant conclusion. Anjana Jimmington ""A Baseline Based Deep Learning Approach of Live Tweets"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23918.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/23918/a-baseline-based-deep-learning-approach-of-live-tweets/anjana-jimmington
E017433538
This document reviews research on predicting personality from Twitter users' tweets using machine learning algorithms. It discusses how tweets have attracted research interest from diverse fields. Different techniques have been used to predict personality from tweets, but there are still shortcomings to address. The aim is to consider the current state of this research area and explore personality prediction from tweets by reviewing past literature and discussing approaches to issues researchers face. It provides an overview of machine learning methods used for personality prediction from tweets, including data collection, preprocessing, model training and evaluation.
NLP journal paper
This document provides a high-level and low-level description of a sentiment analysis system. At the high level, it collects text data, splits it into sentences, assigns polarity, checks for repeated words, and extracts sentiment. The low-level description details how it collects data from Facebook using APIs, processes the data by tagging parts of speech, analyzes polarity vs neutral sets, lists features, and builds a classifier using naive Bayes and dependencies between n-grams and parts of speech. The system aims to analyze sentiment from social media texts at both the document and sentence level.
Recommended
G1803024452
This document discusses analyzing human personality characteristics from social media profiles using machine learning techniques. It collects over 3,000 profile summaries from LinkedIn using web scraping. It then uses the WordNet lexical database to form word clusters for extroversion and introversion characteristics. The k-nearest neighbors algorithm is used to classify profiles as extrovert, introvert, or ambivert based on the words in their summaries. The goal is to analyze users' profiles and provide guidance to write profiles that include a balance of introvert and extrovert traits classified as ambivert, which tends to be viewed more positively. Accuracy results from the classification approach are promising but not discussed in detail.
Social Networking Facebook My Space
The document summarizes a research study that analyzed differences in how older users and teenagers use social networking sites like MySpace. It found that teenagers had larger friend networks focused on their age/interest groups, while older users' networks were more diverse. The study effectively chose the popular MySpace platform and clearly outlined its objective to compare age groups. However, the analysis relied on self-reported profile data, which may not be accurate, and the choice to examine users age 60+ limited useful comparisons as very few in that age group use MySpace.
User Personality Prediction on Facebook Social Media using Machine Learning
In recent years, Social network use is increasingly build up. The various statistics are split widely through social media Such as Facebook, Twitter. Data about the person and what they communicate through the status updates are important for research in human personality. This paper intends to scrutinize the forecasting of personality traits of Facebook users bases on machine learning and part of the Big ve model this experiment uses my personality data set of Facebook users are used for linguistic factors respective to personality correlation. We used the Data Prepossessing concept of data mining after that feature Extraction. Next, we will work on feature selection. The Personality Prediction system built in the XGboosting classi cation model. Poonam L Patil | Dr. S. R. Jadhao "User Personality Prediction on Facebook Social Media using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33414.pdf Paper Url: https://www.ijtsrd.com/computer-science/data-miining/33414/user-personality-prediction-on-facebook-social-media-using-machine-learning/poonam-l-patil
F017433947
This document summarizes a research paper that proposes using a logistic regression classifier trained with stochastic gradient descent to predict Twitter users' personalities from their tweets. It begins with an abstract of the paper and an introduction on personality prediction from social media. It then provides more detail on the anatomy of the research, including defining personality prediction from Twitter, its applications, and the general process of using machine learning for the task. Next, it reviews several previous studies on personality prediction from Twitter and social networks, noting their approaches, findings and limitations. It identifies remaining research gaps, such as the need for improved linguistic analysis of tweets and more robust/scalable predictive models. Finally, it proposes using a logistic regression classifier as the personality prediction model to address
A Baseline Based Deep Learning Approach of Live Tweets
In this scenario social media plays a vital role in influencing the life of people. Twitter , Facebook, Instagram etc are the major social media platforms . They act as a platform for users to raise their opinions on things and events around them. Twitter is one such micro blogging site that allows the user to tweet 6000 tweets per day each of 280 characters long. Data analyst rely on this data to reach conclusion on the events happening around and also to rate a product. But due to massive volume of reviews the analysts find it difficult to go through them and reach at conclusions. In order to solve this problem we adopt the method of sentiment analysis. Sentiment analysis is an approach to classify the sentiment of user reviews, documents etc in terms of positive good , negative bad , neutral surprise . I suggest an enhanced twitter sentiment analysis that retrieves data based on a baseline in a particular pre defined time span and performs sentiment analysis using Textblob . This scheme differs from the traditional and existing one which performs sentiment analysis on pre saved data by performing sentiment analysis on real time data fetched via Twitter API . Thereby providing a much recent and relevant conclusion. Anjana Jimmington ""A Baseline Based Deep Learning Approach of Live Tweets"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23918.pdf
Paper URL: https://www.ijtsrd.com/computer-science/other/23918/a-baseline-based-deep-learning-approach-of-live-tweets/anjana-jimmington
E017433538
This document reviews research on predicting personality from Twitter users' tweets using machine learning algorithms. It discusses how tweets have attracted research interest from diverse fields. Different techniques have been used to predict personality from tweets, but there are still shortcomings to address. The aim is to consider the current state of this research area and explore personality prediction from tweets by reviewing past literature and discussing approaches to issues researchers face. It provides an overview of machine learning methods used for personality prediction from tweets, including data collection, preprocessing, model training and evaluation.
NLP journal paper
This document provides a high-level and low-level description of a sentiment analysis system. At the high level, it collects text data, splits it into sentences, assigns polarity, checks for repeated words, and extracts sentiment. The low-level description details how it collects data from Facebook using APIs, processes the data by tagging parts of speech, analyzes polarity vs neutral sets, lists features, and builds a classifier using naive Bayes and dependencies between n-grams and parts of speech. The system aims to analyze sentiment from social media texts at both the document and sentence level.
Social Group Recommendation based on Big Data
Current life involves physical enjoyment, social activities and content, profile and cyber resources. Now it is easy to merge computing, networking and society with physical systems to create new revolutionary science, technical capabilities and better quality of life. That all possible through Cyber Physical Social Content and Profile Based System (CPSCPs).In this propose system, a group-centric intelligent recommender system named as GroRec, which integrates social, mobile and big data technologies to provide effective, objective and accurate recommendation services. This provides group recommendation in CPSCPs domain. In which activity oriented cluster discovery, the revision of rating information for improved accuracy and cluster preferences modelling that supports descent context mining from multiple sources. Group recommendation is based on profile and content based approach. Our main goal is make several interactions with group members by using specific technique and methods. The recommender system is economical, objective and correct. Ms. Nikita S. Mohite | Mr. H. P. Khandagale"Social Group Recommendation based on Big Data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd7097.pdf http://www.ijtsrd.com/computer-science/data-miining/7097/social-group-recommendation-based-on-big-data/ms-nikita-s-mohite
Analysis
This document summarizes a research study analyzing the impact of social media on employment. The study surveyed 200 employees and student athletes about their social media use, privacy settings, and views on employers monitoring accounts. The introduction discusses how employers are increasingly viewing social media to make hiring decisions. The literature review summarizes several sources discussing both positive and negative consequences of social media use in the workplace. The justification section argues that as social media becomes more integrated into personal and professional life, users must be aware that online content can affect future employment opportunities.
Big five personality prediction based in Indonesian tweets using machine lea...
The popularity of social media has drawn the attention of researchers who have conducted cross-disciplinary studies examining the relationship between personality traits and behavior on social media. Most current work focuses on personality prediction analysis of English texts, but Indonesian has received scant attention. Therefore, this research aims to predict user’s personalities based on Indonesian text from social media using machine learning techniques. This paper evaluates several machine learning techniques, including naive Bayes (NB), K-nearest neighbors (KNN), and support vector machine (SVM), based on semantic features including emotion, sentiment, and publicly available Twitter profile. We predict the personality based on the Big Five personality model, the most appropriate model for predicting user personality in social media. We examine the relationships between the semantic features and the Big Five personality dimensions. The experimental results indicate that the Big Five personality exhibit distinct emotional, sentimental, and social characteristics and that SVM outperformed NB and KNN for Indonesian. In addition, we observe several terms in Indonesian that specifically refer to each personality type, each of which has distinct emotional, sentimental, and social features.
IRJET- Personality Recognition using Social Media Data
This document summarizes a research paper on personality recognition using social media data. The paper proposes analyzing personality traits based on the Big Five model (openness, conscientiousness, extraversion, agreeableness, neuroticism) using Facebook status updates and machine learning. Specifically, it involves collecting Facebook status data through a browser extension, storing it in a database, training a random forest regression model on an existing dataset, and using the model to predict personality trait values for additional Facebook users. The predicted traits are then visualized with radar charts to provide an overview of each user's personality profile.
Unit 35
The document provides information about Instagram, including:
1) Instagram began as a photo sharing app that allowed square images only and short videos, but has since expanded the types of images and longer videos that can be shared.
2) Instagram was acquired by Facebook in 2012 for $1 billion.
3) Instagram has over 500 million active users and aims to allow users to "capture and share the world's moments."
Unit 35
The document provides information about Instagram, including:
1) Instagram began as a photo sharing app that allowed square images only and short videos, but has since expanded the types of images and longer videos that can be shared.
2) Instagram was acquired by Facebook in 2012 for $1 billion.
3) Instagram has over 500 million active users and aims to allow users to "capture and share the world's moments."
Unit 35
The document provides information about Instagram, including:
1) Instagram began as a photo sharing app that allowed square images only and short videos, but has since expanded the types of images and longer videos that can be shared.
2) Instagram was acquired by Facebook in 2012 for $1 billion.
3) Instagram has over 500 million active users and aims to allow users to "capture and share the world's moments."
Empowering Caregivers
This study analyzed 500 Instagram posts with the hashtag #Microcephaly to understand how caregivers of patients with microcephaly use social media. The majority of posts showed female patients and their mothers engaging in daily routines. Caregivers used Instagram to share information, celebrate milestones, fundraise, and provide social support to cope with caring for patients. Hashtags and captions were mostly positive and focused on love, faith, and patients' progress. The study found Instagram is an accessible and empowering tool for caregivers.
Sentiment Analysis on Twitter Dataset using R Language
Sentiment Analysis involves determining the evaluative nature of a piece of text. A product review can express a positive, negative, or neutral sentiment or polarity . Automatically identifying sentiment expressed in text has a number of applications, including tracking sentiment towards Movie reviews and Automobile reviews improving customer relation models, detecting happiness and well being, and improving automatic dialogue systems. The evaluative intensity for both positive and negative terms changes in a negated context, and the amount of change varies from term to term. To adequately capture the impact of negation on individual terms, here proposed to empirically estimate the sentiment scores of terms in negated context from movie review and auto mobile review, and built two lexicons, one for terms in negated contexts and one for terms in affirmative non negated contexts. By using these Affirmative Context Lexicons and Negated Context Lexicons were able to significantly improve the performance of the overall sentiment analysis system on both tasks. This thesis have proposed a sentiment analysis system that detects the sentiment of corpus dataset using movie review and Automobile review as well as the sentiment of a term a word or a phrase within a message term level task using R language. B. Nagajothi | Dr. R. Jemima Priyadarsini "Sentiment Analysis on Twitter Dataset using R Language" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28071.pdf Paper URL: https://www.ijtsrd.com/computer-science/data-miining/28071/sentiment-analysis-on-twitter-dataset-using-r-language/b-nagajothi
209
This document discusses using text mining of online social networks to classify user personality traits. It examines using status updates from Facebook profiles as text data to extract features and classify personalities according to the Big Five model using an RBF neural network. The results showed RBF neural networks achieved higher precision than other common classifiers like SVM and Naive Bayes.
Googlization
The passage discusses Nicholas Carr's book "The Shallows" and how it analyzes the impact of technology on learning processes. Specifically, it focuses on Chapter 8 which looks at how search engines like Google have revolutionized knowledge organization by providing access to vast information online. While search engines offer benefits of accessibility, Carr is also wary of their control over knowledge and how heavily people now rely on them. The passage provides background on how Google was created and how its business model relies on efficiency principles from Frederick Taylor.
Data analytics in instagram
Instagram is an application that we use everyday. Instagram uses data analytics to capture consumers attention.
JFrank_1
This document discusses developing social media strategies across multiple platforms. It analyzes data from Facebook, Twitter and Instagram pages of three brands (Herschel Supply, Jansport and Yeti Coolers) over six weeks. The analysis found Instagram is best for building branded communities around consumer products. It identifies influencers and regional trends. The document provides models for social media resource allocation and strategic influencer marketing based on the findings.
Unit 35 james pickering
Instagram is a social media platform launched in 2010 that allows users to share photos and 60-second videos. It was acquired by Facebook in 2012 for $1 billion. The app originally only allowed square images but was updated in 2015 to support different image sizes and longer videos. It has over 500 million active users and is most popular among 18-24 year olds. Users can share content publicly or privately and view content from others. The platform also generates revenue through sponsored posts targeted towards specific demographics.
Unit3511 170427151808
Instagram is a social media platform launched in 2010 that allows users to share photos and 60-second videos. It was acquired by Facebook in 2012 for $1 billion. The app originally only allowed square images but was updated in 2015 to support different image sizes and longer videos. It has over 500 million active users and is most popular among 18-24 year olds. Users can share content publicly or privately and view content from others. The platform also generates revenue through sponsored posts targeted towards specific demographics.
My new proposal (1).docx
Social media platforms allow for widespread sharing of information but also enable the spread of criminal and unethical ideas. This document proposes a social media analysis tool to detect crime and suspicious profiles on platforms like Twitter. The tool would extract tweet data using APIs, analyze features to identify concerning behaviors, perform topic modeling to detect tweets related to crime, and suggest profiles for suspension. The goal is to prevent the spread of criminal content and activities online through monitoring social media data and flagging problematic accounts.
Identifying ghost users using social media metadata - University College London
You are your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information a joint research project of the Alan Turing Institute and University College in London
final
This document summarizes a research study on the impact of social media on future employment. The study surveyed 200 employees and student athletes about their social media use and privacy settings. It analyzed how discretion on social media platforms like Twitter, Instagram, and Facebook could affect employment and eligibility to play sports. The research found that social media posts can invade privacy and restrict self-expression, and that many users are unaware of how their online actions could impact their careers or status as athletes. The document reviews several other studies that similarly examine how employers use social media for hiring decisions and how content online can negatively influence jobs and evaluations.
SENTIMENT ANALYSIS OF TWITTER DATA
This document summarizes a research project on sentiment analysis of tweets about news. The researchers collected tweets related to news articles from various sources and analyzed the sentiment of the tweets to determine the overall public sentiment toward that news. They first preprocessed the tweet text through tokenization, removed stopwords, and calculated term frequencies. Next, they analyzed term co-occurrences to understand context. They also created visualizations of frequent terms. Finally, they used a naive Bayes classifier trained on labeled data to classify tweets in real-time as positive, negative, or neutral sentiment toward the news. The system aimed to provide a score indicating overall public sentiment toward each news article based on related tweets.
REAL TIME SENTIMENT ANALYSIS OF TWITTER DATA
With the rise of social networking epoch, there has been a surge of user generated content. Micro blogging sites have millions of people sharing their thoughts daily because of its characteristic short and simple manner of expression. We propose and investigate a paradigm to mine the sentiment from a popular real-time micro blogging service, Twitter, where users post real time reactions to and opinions about “everything”. In this paper, we expound a hybrid approach using both corpus based and dictionary based methods to determine the semantic orientation of the opinion words in tweets. A case study is presented to illustrate the use and effectiveness of the proposed system.
Distributed State Estimation With Deep Neural Networks for Uncertain Nonlinea...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Distributed Inference in Resource-Constrained IoT for Real-Time Video Surveil...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
More Related Content
Similar to A Deep Multimodal Learning Approach to Perceive Basic Needs of Humans From Instagram Profile.pdf
Social Group Recommendation based on Big Data
Current life involves physical enjoyment, social activities and content, profile and cyber resources. Now it is easy to merge computing, networking and society with physical systems to create new revolutionary science, technical capabilities and better quality of life. That all possible through Cyber Physical Social Content and Profile Based System (CPSCPs).In this propose system, a group-centric intelligent recommender system named as GroRec, which integrates social, mobile and big data technologies to provide effective, objective and accurate recommendation services. This provides group recommendation in CPSCPs domain. In which activity oriented cluster discovery, the revision of rating information for improved accuracy and cluster preferences modelling that supports descent context mining from multiple sources. Group recommendation is based on profile and content based approach. Our main goal is make several interactions with group members by using specific technique and methods. The recommender system is economical, objective and correct. Ms. Nikita S. Mohite | Mr. H. P. Khandagale"Social Group Recommendation based on Big Data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd7097.pdf http://www.ijtsrd.com/computer-science/data-miining/7097/social-group-recommendation-based-on-big-data/ms-nikita-s-mohite
Analysis
This document summarizes a research study analyzing the impact of social media on employment. The study surveyed 200 employees and student athletes about their social media use, privacy settings, and views on employers monitoring accounts. The introduction discusses how employers are increasingly viewing social media to make hiring decisions. The literature review summarizes several sources discussing both positive and negative consequences of social media use in the workplace. The justification section argues that as social media becomes more integrated into personal and professional life, users must be aware that online content can affect future employment opportunities.
Big five personality prediction based in Indonesian tweets using machine lea...
The popularity of social media has drawn the attention of researchers who have conducted cross-disciplinary studies examining the relationship between personality traits and behavior on social media. Most current work focuses on personality prediction analysis of English texts, but Indonesian has received scant attention. Therefore, this research aims to predict user’s personalities based on Indonesian text from social media using machine learning techniques. This paper evaluates several machine learning techniques, including naive Bayes (NB), K-nearest neighbors (KNN), and support vector machine (SVM), based on semantic features including emotion, sentiment, and publicly available Twitter profile. We predict the personality based on the Big Five personality model, the most appropriate model for predicting user personality in social media. We examine the relationships between the semantic features and the Big Five personality dimensions. The experimental results indicate that the Big Five personality exhibit distinct emotional, sentimental, and social characteristics and that SVM outperformed NB and KNN for Indonesian. In addition, we observe several terms in Indonesian that specifically refer to each personality type, each of which has distinct emotional, sentimental, and social features.
IRJET- Personality Recognition using Social Media Data
This document summarizes a research paper on personality recognition using social media data. The paper proposes analyzing personality traits based on the Big Five model (openness, conscientiousness, extraversion, agreeableness, neuroticism) using Facebook status updates and machine learning. Specifically, it involves collecting Facebook status data through a browser extension, storing it in a database, training a random forest regression model on an existing dataset, and using the model to predict personality trait values for additional Facebook users. The predicted traits are then visualized with radar charts to provide an overview of each user's personality profile.
Unit 35
The document provides information about Instagram, including:
1) Instagram began as a photo sharing app that allowed square images only and short videos, but has since expanded the types of images and longer videos that can be shared.
2) Instagram was acquired by Facebook in 2012 for $1 billion.
3) Instagram has over 500 million active users and aims to allow users to "capture and share the world's moments."
Unit 35
The document provides information about Instagram, including:
1) Instagram began as a photo sharing app that allowed square images only and short videos, but has since expanded the types of images and longer videos that can be shared.
2) Instagram was acquired by Facebook in 2012 for $1 billion.
3) Instagram has over 500 million active users and aims to allow users to "capture and share the world's moments."
Unit 35
The document provides information about Instagram, including:
1) Instagram began as a photo sharing app that allowed square images only and short videos, but has since expanded the types of images and longer videos that can be shared.
2) Instagram was acquired by Facebook in 2012 for $1 billion.
3) Instagram has over 500 million active users and aims to allow users to "capture and share the world's moments."
Empowering Caregivers
This study analyzed 500 Instagram posts with the hashtag #Microcephaly to understand how caregivers of patients with microcephaly use social media. The majority of posts showed female patients and their mothers engaging in daily routines. Caregivers used Instagram to share information, celebrate milestones, fundraise, and provide social support to cope with caring for patients. Hashtags and captions were mostly positive and focused on love, faith, and patients' progress. The study found Instagram is an accessible and empowering tool for caregivers.
Sentiment Analysis on Twitter Dataset using R Language
Sentiment Analysis involves determining the evaluative nature of a piece of text. A product review can express a positive, negative, or neutral sentiment or polarity . Automatically identifying sentiment expressed in text has a number of applications, including tracking sentiment towards Movie reviews and Automobile reviews improving customer relation models, detecting happiness and well being, and improving automatic dialogue systems. The evaluative intensity for both positive and negative terms changes in a negated context, and the amount of change varies from term to term. To adequately capture the impact of negation on individual terms, here proposed to empirically estimate the sentiment scores of terms in negated context from movie review and auto mobile review, and built two lexicons, one for terms in negated contexts and one for terms in affirmative non negated contexts. By using these Affirmative Context Lexicons and Negated Context Lexicons were able to significantly improve the performance of the overall sentiment analysis system on both tasks. This thesis have proposed a sentiment analysis system that detects the sentiment of corpus dataset using movie review and Automobile review as well as the sentiment of a term a word or a phrase within a message term level task using R language. B. Nagajothi | Dr. R. Jemima Priyadarsini "Sentiment Analysis on Twitter Dataset using R Language" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28071.pdf Paper URL: https://www.ijtsrd.com/computer-science/data-miining/28071/sentiment-analysis-on-twitter-dataset-using-r-language/b-nagajothi
209
This document discusses using text mining of online social networks to classify user personality traits. It examines using status updates from Facebook profiles as text data to extract features and classify personalities according to the Big Five model using an RBF neural network. The results showed RBF neural networks achieved higher precision than other common classifiers like SVM and Naive Bayes.
Googlization
The passage discusses Nicholas Carr's book "The Shallows" and how it analyzes the impact of technology on learning processes. Specifically, it focuses on Chapter 8 which looks at how search engines like Google have revolutionized knowledge organization by providing access to vast information online. While search engines offer benefits of accessibility, Carr is also wary of their control over knowledge and how heavily people now rely on them. The passage provides background on how Google was created and how its business model relies on efficiency principles from Frederick Taylor.
Data analytics in instagram
Instagram is an application that we use everyday. Instagram uses data analytics to capture consumers attention.
JFrank_1
This document discusses developing social media strategies across multiple platforms. It analyzes data from Facebook, Twitter and Instagram pages of three brands (Herschel Supply, Jansport and Yeti Coolers) over six weeks. The analysis found Instagram is best for building branded communities around consumer products. It identifies influencers and regional trends. The document provides models for social media resource allocation and strategic influencer marketing based on the findings.
Unit 35 james pickering
Instagram is a social media platform launched in 2010 that allows users to share photos and 60-second videos. It was acquired by Facebook in 2012 for $1 billion. The app originally only allowed square images but was updated in 2015 to support different image sizes and longer videos. It has over 500 million active users and is most popular among 18-24 year olds. Users can share content publicly or privately and view content from others. The platform also generates revenue through sponsored posts targeted towards specific demographics.
Unit3511 170427151808
Instagram is a social media platform launched in 2010 that allows users to share photos and 60-second videos. It was acquired by Facebook in 2012 for $1 billion. The app originally only allowed square images but was updated in 2015 to support different image sizes and longer videos. It has over 500 million active users and is most popular among 18-24 year olds. Users can share content publicly or privately and view content from others. The platform also generates revenue through sponsored posts targeted towards specific demographics.
My new proposal (1).docx
Social media platforms allow for widespread sharing of information but also enable the spread of criminal and unethical ideas. This document proposes a social media analysis tool to detect crime and suspicious profiles on platforms like Twitter. The tool would extract tweet data using APIs, analyze features to identify concerning behaviors, perform topic modeling to detect tweets related to crime, and suggest profiles for suspension. The goal is to prevent the spread of criminal content and activities online through monitoring social media data and flagging problematic accounts.
Identifying ghost users using social media metadata - University College London
You are your Metadata: Identification and Obfuscation of Social Media Users using Metadata Information a joint research project of the Alan Turing Institute and University College in London
final
This document summarizes a research study on the impact of social media on future employment. The study surveyed 200 employees and student athletes about their social media use and privacy settings. It analyzed how discretion on social media platforms like Twitter, Instagram, and Facebook could affect employment and eligibility to play sports. The research found that social media posts can invade privacy and restrict self-expression, and that many users are unaware of how their online actions could impact their careers or status as athletes. The document reviews several other studies that similarly examine how employers use social media for hiring decisions and how content online can negatively influence jobs and evaluations.
SENTIMENT ANALYSIS OF TWITTER DATA
This document summarizes a research project on sentiment analysis of tweets about news. The researchers collected tweets related to news articles from various sources and analyzed the sentiment of the tweets to determine the overall public sentiment toward that news. They first preprocessed the tweet text through tokenization, removed stopwords, and calculated term frequencies. Next, they analyzed term co-occurrences to understand context. They also created visualizations of frequent terms. Finally, they used a naive Bayes classifier trained on labeled data to classify tweets in real-time as positive, negative, or neutral sentiment toward the news. The system aimed to provide a score indicating overall public sentiment toward each news article based on related tweets.
REAL TIME SENTIMENT ANALYSIS OF TWITTER DATA
With the rise of social networking epoch, there has been a surge of user generated content. Micro blogging sites have millions of people sharing their thoughts daily because of its characteristic short and simple manner of expression. We propose and investigate a paradigm to mine the sentiment from a popular real-time micro blogging service, Twitter, where users post real time reactions to and opinions about “everything”. In this paper, we expound a hybrid approach using both corpus based and dictionary based methods to determine the semantic orientation of the opinion words in tweets. A case study is presented to illustrate the use and effectiveness of the proposed system.
Similar to A Deep Multimodal Learning Approach to Perceive Basic Needs of Humans From Instagram Profile.pdf (20)
Big five personality prediction based in Indonesian tweets using machine lea...
Big five personality prediction based in Indonesian tweets using machine lea...
IRJET- Personality Recognition using Social Media Data
IRJET- Personality Recognition using Social Media Data
Sentiment Analysis on Twitter Dataset using R Language
Sentiment Analysis on Twitter Dataset using R Language
Identifying ghost users using social media metadata - University College London
Identifying ghost users using social media metadata - University College London
More from OKOKPROJECTS
Distributed State Estimation With Deep Neural Networks for Uncertain Nonlinea...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Distributed Inference in Resource-Constrained IoT for Real-Time Video Surveil...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
DLTIF Deep Learning-Driven Cyber Threat Intelligence Modeling and Identificat...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
DGSSC A Deep Generative Spectral-Spatial Classifier for Imbalanced Hyperspect...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Digital Restoration of Cultural Heritage With Data-Driven Computing A Survey.pdf
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Dependable Intrusion Detection System for IoT A Deep Transfer Learning Based ...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
DendroMap Visual Exploration of Large-Scale Image Datasets for Machine Learni...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Dense Nested Attention Network for Infrared Small Target Detection.pdf
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Detection of Small Moving Targets in Cluttered Infrared Imagery.pdf
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Depression Screening in Humans With AI and Deep Learning Techniques.pdf
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
DeepTx Deep Learning Beamforming With Channel Prediction.pdf
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
DeHIN A Decentralized Framework for Embedding Large-Scale Heterogeneous Infor...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
DefQ Defensive Quantization Against Inference Slow-Down Attack for Edge Compu...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Deep-Learning-Driven Proactive Maintenance Management of IoT-Empowered Smart ...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Deep-Distributed-Learning-Based POI Recommendation Under Mobile-Edge Networks...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
DeepCog A Trustworthy Deep Learning-Based Human Cognitive Privacy Framework i...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
DeepCrowd A Deep Model for Large-Scale Citywide Crowd Density and Flow Predic...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
D2Net Deep Denoising Network in Frequency Domain for Hyperspectral Image.pdf
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Decentralized Federated Learning for Industrial IoT With Deep Echo State Netw...
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
Cyber Code Intelligence for Android Malware Detection.pdf
https://okokprojects.com/
IEEE PROJECTS 2023-2024 TITLE LIST
WhatsApp : +91-8144199666
From Our Title List the Cost will be,
Mail Us: okokprojects@gmail.com
Website: : https://www.okokprojects.com
: http://www.ieeeproject.net
Support Including Packages
=======================
* Complete Source Code
* Complete Documentation
* Complete Presentation Slides
* Flow Diagram
* Database File
* Screenshots
* Execution Procedure
* Video Tutorials
* Supporting Softwares
Support Specialization
=======================
* 24/7 Support
* Ticketing System
* Voice Conference
* Video On Demand
* Remote Connectivity
* Document Customization
* Live Chat Support
More from OKOKPROJECTS (20)
Distributed State Estimation With Deep Neural Networks for Uncertain Nonlinea...
Distributed State Estimation With Deep Neural Networks for Uncertain Nonlinea...
Distributed Inference in Resource-Constrained IoT for Real-Time Video Surveil...
Distributed Inference in Resource-Constrained IoT for Real-Time Video Surveil...
DLTIF Deep Learning-Driven Cyber Threat Intelligence Modeling and Identificat...
DLTIF Deep Learning-Driven Cyber Threat Intelligence Modeling and Identificat...
DGSSC A Deep Generative Spectral-Spatial Classifier for Imbalanced Hyperspect...
DGSSC A Deep Generative Spectral-Spatial Classifier for Imbalanced Hyperspect...
Digital Restoration of Cultural Heritage With Data-Driven Computing A Survey.pdf
Digital Restoration of Cultural Heritage With Data-Driven Computing A Survey.pdf
Dependable Intrusion Detection System for IoT A Deep Transfer Learning Based ...
Dependable Intrusion Detection System for IoT A Deep Transfer Learning Based ...
DendroMap Visual Exploration of Large-Scale Image Datasets for Machine Learni...
DendroMap Visual Exploration of Large-Scale Image Datasets for Machine Learni...
Dense Nested Attention Network for Infrared Small Target Detection.pdf
Dense Nested Attention Network for Infrared Small Target Detection.pdf
Detection of Small Moving Targets in Cluttered Infrared Imagery.pdf
Detection of Small Moving Targets in Cluttered Infrared Imagery.pdf
Depression Screening in Humans With AI and Deep Learning Techniques.pdf
Depression Screening in Humans With AI and Deep Learning Techniques.pdf
DeepTx Deep Learning Beamforming With Channel Prediction.pdf
DeepTx Deep Learning Beamforming With Channel Prediction.pdf
DeHIN A Decentralized Framework for Embedding Large-Scale Heterogeneous Infor...
DeHIN A Decentralized Framework for Embedding Large-Scale Heterogeneous Infor...
DefQ Defensive Quantization Against Inference Slow-Down Attack for Edge Compu...
DefQ Defensive Quantization Against Inference Slow-Down Attack for Edge Compu...
Deep-Learning-Driven Proactive Maintenance Management of IoT-Empowered Smart ...
Deep-Learning-Driven Proactive Maintenance Management of IoT-Empowered Smart ...
Deep-Distributed-Learning-Based POI Recommendation Under Mobile-Edge Networks...
Deep-Distributed-Learning-Based POI Recommendation Under Mobile-Edge Networks...
DeepCog A Trustworthy Deep Learning-Based Human Cognitive Privacy Framework i...
DeepCog A Trustworthy Deep Learning-Based Human Cognitive Privacy Framework i...
DeepCrowd A Deep Model for Large-Scale Citywide Crowd Density and Flow Predic...
DeepCrowd A Deep Model for Large-Scale Citywide Crowd Density and Flow Predic...
D2Net Deep Denoising Network in Frequency Domain for Hyperspectral Image.pdf
D2Net Deep Denoising Network in Frequency Domain for Hyperspectral Image.pdf
Decentralized Federated Learning for Industrial IoT With Deep Echo State Netw...
Decentralized Federated Learning for Industrial IoT With Deep Echo State Netw...
Cyber Code Intelligence for Android Malware Detection.pdf
Cyber Code Intelligence for Android Malware Detection.pdf
Recently uploaded
How to Make a Field Mandatory in Odoo 17
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Aberdeen
clinical examination of hip joint (1).pdf
described clinical examination all orthopeadic conditions .
PCOS corelations and management through Ayurveda.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
Community pharmacy- Social and preventive pharmacy UNIT 5
Covered community pharmacy topic of the subject Social and preventive pharmacy for Diploma and Bachelor of pharmacy
DRUGS AND ITS classification slide share
Any substance (other than food) that is used to prevent, diagnose, treat, or relieve symptoms of a
disease or abnormal condition
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...Nguyen Thanh Tu Collection
https://app.box.com/s/y977uz6bpd3af4qsebv7r9b7s21935vdLAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
How to Add Chatter in the odoo 17 ERP Module
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
How to Fix the Import Error in the Odoo 17
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
How to Setup Warehouse & Location in Odoo 17 Inventory
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS Template 2023-2024 by: Irene S. Rueco
Recently uploaded (20)
Digital Artefact 1 - Tiny Home Environmental Design
Digital Artefact 1 - Tiny Home Environmental Design
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
Community pharmacy- Social and preventive pharmacy UNIT 5
Community pharmacy- Social and preventive pharmacy UNIT 5
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
Liberal Approach to the Study of Indian Politics.pdf
Liberal Approach to the Study of Indian Politics.pdf
How to Setup Warehouse & Location in Odoo 17 Inventory
How to Setup Warehouse & Location in Odoo 17 Inventory
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
A Deep Multimodal Learning Approach to Perceive Basic Needs of Humans From Instagram Profile.pdf
- 1. A Deep Multimodal Learning Approach to Perceive Basic Needs of Humans From Instagram Profile Abstract Nowadays, a significant part of our time is spent sharing multimodal data on social media sites such as Instagram, Facebook way through which users present themselves to social media can provide useful insights into their behaviours, personalities, perspectives, motives and needs. This article proposes to use multimodal data collected from Instagram accounts to predict the five basic prototypical needs described in Glasser's choice theory (i.e., Survival , Power , Freedom , Belonging , and Fun ). We automate the identification of the unconsciously perceived needs from Instagram profiles by using both approach aggregates the visual and textual features extracted using deep learning and constructs a homogeneous representation for each profile through the proposed Bag classification on the fusion of both modalities. We validate our proposal on a large database, consensually annotated by two expert psychologists, with A Deep Multimodal Learning Approach to Perceive Basic Needs of Humans From Instagram Profile Nowadays, a significant part of our time is spent sharing multimodal data on social media sites such as Instagram, Facebook and Twitter. The particular way through which users present themselves to social media can provide useful insights into their behaviours, personalities, perspectives, motives and needs. This article proposes to use multimodal data collected from Instagram accounts to predict the five basic prototypical needs described in Glasser's choice theory (i.e., Survival , Power , Freedom , Belonging , and Fun ). We automate the identification of the unconsciously perceived needs from Instagram profiles by using both visual and textual contents. The proposed approach aggregates the visual and textual features extracted using deep learning and constructs a homogeneous representation for each profile through the proposed Bag-of-Content . Finally, we perform multi classification on the fusion of both modalities. We validate our proposal on a large database, consensually annotated by two expert psychologists, with A Deep Multimodal Learning Approach to Perceive Basic Needs of Humans Nowadays, a significant part of our time is spent sharing multimodal data on and Twitter. The particular way through which users present themselves to social media can provide useful insights into their behaviours, personalities, perspectives, motives and needs. This article proposes to use multimodal data collected from Instagram accounts to predict the five basic prototypical needs described in Glasser's choice theory (i.e., Survival , Power , Freedom , Belonging , and Fun ). We automate the identification of the unconsciously perceived needs from visual and textual contents. The proposed approach aggregates the visual and textual features extracted using deep learning and constructs a homogeneous representation for each profile Content . Finally, we perform multi-label classification on the fusion of both modalities. We validate our proposal on a large database, consensually annotated by two expert psychologists, with
- 2. more than 30,000 images, captions and comments. Experiments show promising accuracy and complementary information between visual and textual cues.