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
www.scirp.org/journal/jdaip
E-mail: jdaip@scirp.org

Google-based Impact Factor: 3.58
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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):

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[71]	Followers Are Not Enough: A Multifaceted Approach to Community Detection in Online Social Networks
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[72]	Image Understanding by Socializing the Semantic Gap
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[73]	Machine learning and sentiment analysis approaches for the analysis of Parliamentary debates.
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[74]	基于相似度的微博社交网络的社区发现方法
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[75]	Followers Are Not Enough: Beyond Structural Communities in Online Social Networks
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[76]	Twitter Sentiment in Data Streams with Perceptron
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[77]	Sentiment Analysis on the Social Networks Using Stream Algorithms
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[78]	Followers Are Not Enough: A Question-Oriented Approach to Community Detection in Online Social Networks
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[79]	Machine Learning and Sentiment Analysis Approaches for the Analysis of Parliamentary Debates
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[80]	Followers Are Not Enough: Beyond Structural Communities in Online Social Networks.
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[81]	Evaluation datasets for twitter sentiment analysis: a survey and a new dataset, the sts-gold
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[82]	Evaluation datasets for twitter sentiment analysis
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[5]	Capturing stance dynamics in social media: open challenges and research directions International Journal of Digital Humanities, 2022 DOI:10.1007/s42803-022-00043-w

[6]	A Feature-Based Approach for Sentiment Quantification Using Machine Learning Electronics, 2022 DOI:10.3390/electronics11060846

[7]	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

[8]	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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[10]	Community Detection and Impact of Bots on Sentiment Polarity of Twitter Networks 2021 Asian Conference on Innovation in Technology (ASIANCON), 2021 DOI:10.1109/ASIANCON51346.2021.9544691

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

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

[13]	Interaction Communities in Blockchain Online Social Media 2021 Third International Conference on Blockchain Computing and Applications (BCCA), 2021 DOI:10.1109/BCCA53669.2021.9657049

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

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

[16]	#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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[20]	MixedEmotions: An Open-Source Toolbox for Multimodal Emotion Analysis IEEE Transactions on Multimedia, 2018 DOI:10.1109/TMM.2018.2798287

[21]	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

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

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

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

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

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

[27]	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

[28]	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

[29]	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 - GJH&GC '16, 2016 DOI:10.1145/2897167.2897178

[30]	Handbook of Operations Analytics Using Data Envelopment Analysis International Series in Operations Research & Management Science, 2016 DOI:10.1007/978-1-4899-7705-2_17

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

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

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

Follow SCIRP

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	+86 18163351462(WhatsApp)
	1655362766

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