Mutually Enhancing Community Detection and Sentiment Analysis on Twitter Networks

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Journal of Data Analysis and Information Processing

ISSN Print: 2327-7211
ISSN Online: 2327-7203
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"Mutually Enhancing Community Detection and Sentiment Analysis on Twitter Networks"
written by William Deitrick, Wei Hu,
published by Journal of Data Analysis and Information Processing, Vol.1 No.3, 2013

has been cited by the following article(s):

Google Scholar
CrossRef

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[4]	Detection of Hidden Communities in Twitter Discussions of Varying Volumes
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[9]	Using Twitter to explore consumers' sentiments and their social representations towards new food trends
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[10]	Multilingual stance detection in social media political debates
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[11]	CRANK: A Hybrid Model for User and Content Sentiment Classification Using Social Context and Community Detection
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[13]	An Experimental Study on Performance of Text Representation Models for Sentiment Analysis
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[14]	Second International Symposium on Platial Information Science
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[15]	Community Based Emotional Behaviour Using Ekman's Emotional Scale
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[16]	# Brexit: Leave or remain? the role of user's community and diachronic evolution on stance detection
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[17]	Investigating Political Herd Mentality: A Community Sentiment Based Approach
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[18]	Social context in sentiment analysis: Formal definition, overview of current trends and framework for comparison
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[19]	Community Structure-based Re-ranking Information Influence Maximization Algorithm for Typhoon Disasters.
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[20]	Graph-based Community Detection in Social Network
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[21]	Social Network Sentiment Analysis and Message Clustering
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[22]	Ontology-based sentiment analysis and community detection on social media: application to Brexit
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[30]	Different Anti-Vaping Campaigns Attracting the Same Opponent Community
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[33]	From interaction to participation: the role of the imagined audience in social media community detection and an application to political communication on Twitter
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[36]	Geotagging matters?
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[41]	People Opinion Topic Model: Opinion based User Clustering in Social Networks
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[43]	Community detection on anti-vaping campaign audience
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[48]	Using Sentiment Analysis to track reaction to the Global Game Jam Theme
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[49]	Like it or not: A survey of twitter sentiment analysis methods
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[50]	Detecting Communities of Interests in Social Media Platforms using Genetic Algorithms
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[51]	Evaluative Language Beyond Bags of Words: Linguistic Insights and Computational Applications
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[52]	Improving Twitter Community Detection through Contextual Sentiment Analysis
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[53]	Combining topological and topical features for community detection
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[54]	Improving Twitter Community Detection through Contextual Sentiment Analysis of Tweets
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[55]	Semantic Sentiment Analysis of Mircroblogs
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[56]	An improved density peaks-based clustering method for social circle discovery in social networks
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[57]	基于节点亲密度和度的社会网络社团发现方法
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[58]	Ανάλυση Συναισθήματος Σε Κείμενο Από Tweets Με Μεθόδους Μη Επιβλεπόμενης Μηχανικής Μάθησης
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[59]	A multimodal feature learning approach for sentiment analysis of social network multimedia
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[60]	Followers Are Not Enough: A Multifaceted Approach to Community Detection in Online Social Networks
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[61]	Image Understanding by Socializing the Semantic Gap
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[62]	Machine learning and sentiment analysis approaches for the analysis of Parliamentary debates.
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[63]	基于相似度的微博社交网络的社区发现方法
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[64]	Followers Are Not Enough: Beyond Structural Communities in Online Social Networks
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[65]	Twitter Sentiment in Data Streams with Perceptron
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[66]	Sentiment Analysis on the Social Networks Using Stream Algorithms
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[67]	Followers Are Not Enough: A Question-Oriented Approach to Community Detection in Online Social Networks
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[68]	Machine Learning and Sentiment Analysis Approaches for the Analysis of Parliamentary Debates
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[69]	Evaluation datasets for twitter sentiment analysis: a survey and a new dataset, the sts-gold
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[70]	Evaluation datasets for twitter sentiment analysis
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[5]	Using Twitter to explore consumers' sentiments and their social representations towards new food trends British Food Journal, 2021 DOI:10.1108/BFJ-03-2020-0192

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[9]	Detection of Hidden Communities in Twitter Discussions of Varying Volumes Future Internet, 2021 DOI:10.3390/fi13110295

[10]	Making sense of tweets using sentiment analysis on closely related topics Social Network Analysis and Mining, 2021 DOI:10.1007/s13278-021-00752-0

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[12]	Multilingual Stance Detection in Social Media Political Debates Computer Speech & Language, 2020 DOI:10.1016/j.csl.2020.101075

[13]	CRANK: A Hybrid Model for User and Content Sentiment Classification Using Social Context and Community Detection Applied Sciences, 2020 DOI:10.3390/app10051662

[14]	#Brexit: Leave or remain? the role of user’s community and diachronic evolution on stance detection Journal of Intelligent & Fuzzy Systems, 2020 DOI:10.3233/JIFS-179895

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[18]	MixedEmotions: An Open-Source Toolbox for Multimodal Emotion Analysis IEEE Transactions on Multimedia, 2018 DOI:10.1109/TMM.2018.2798287

[19]	Introduction to the Special Issue on Language in Social Media: Exploiting Discourse and Other Contextual Information Computational Linguistics, 2018 DOI:10.1162/coli_a_00333

[20]	Different Anti-Vaping Campaigns Attracting the Same Opponent Community IEEE Transactions on NanoBioscience, 2018 DOI:10.1109/TNB.2018.2855157

[21]	Evaluative Language Beyond Bags of Words: Linguistic Insights and Computational Applications Computational Linguistics, 2017 DOI:10.1162/COLI_a_00278

[22]	People Opinion Topic Model Proceedings of the 26th International Conference on World Wide Web Companion - WWW '17 Companion, 2017 DOI:10.1145/3041021.3051159

[23]	Community detection on anti-vaping campaign audience 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017 DOI:10.1109/BIBM.2017.8217774

[24]	Like It or Not ACM Computing Surveys, 2017 DOI:10.1145/2938640

[25]	Using Sentiment Analysis to track reaction to the Global Game Jam Theme Proceedings of the International Conference on Game Jams, Hackathons, and Game Creation Events, 2016 DOI:10.1145/2897167.2897178

[26]	Combining topological and topical features for community detection 2016 International Conference on Advanced Computer Science and Information Systems (ICACSIS), 2016 DOI:10.1109/ICACSIS.2016.7872775

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[29]	Like It or Not ACM Computing Surveys, 2016 DOI:10.1145/2938640

[30]	Sentiment Analysis on the Social Networks Using Stream Algorithms Journal of Data Analysis and Information Processing, 2014 DOI:10.4236/jdaip.2014.22008

[31]	Twitter Sentiment in Data Streams with Perceptron Journal of Computer and Communications, 2014 DOI:10.4236/jcc.2014.23002

Follow SCIRP

	+1 323-425-8868
	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

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