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Measuring node importance on Twitter microblogging

Published: 13 June 2012 Publication History

Abstract

Social Networks (SN) are created whenever people interact with other people in online social networks, such as Twitter, Google+, Facebook and etc. Twitter is a social networking and micro-blogging service; it creates several new interesting social network structures. In this sense, our main goal is to investigate the power of retweet mechanism. The findings suggest that relations of "friendship" at Twitter are important but not enough. Still, the centrality measures of a node importance do not show how important users are. We uncovered some other principles that must be studied like, homophily phenomenon, the tendency of individuals to associate and bond with similar others.

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    cover image ACM Other conferences
    WIMS '12: Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
    June 2012
    571 pages
    ISBN:9781450309158
    DOI:10.1145/2254129
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    • UCV: University of Craiova
    • WNRI: Western Norway Research Institute

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    Association for Computing Machinery

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    Publication History

    Published: 13 June 2012

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    Author Tags

    1. Twitter
    2. node importance
    3. retweet
    4. social network analysis

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    • WNRI

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    Cited By

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    • (2025)I know your stance! Analyzing Twitter users’ political stance on diverse perspectivesJournal of Big Data10.1186/s40537-025-01083-z12:1Online publication date: 26-Jan-2025
    • (2023)An Influential User Prediction in Social Network Using Centrality Measures and Deep Learning MethodProceedings of Data Analytics and Management10.1007/978-981-19-7615-5_66(813-829)Online publication date: 25-Mar-2023
    • (2022)Influencers Analysis from Social Media Data2022 International Conference on Artificial Intelligence and Data Engineering (AIDE)10.1109/AIDE57180.2022.10059732(217-222)Online publication date: 22-Dec-2022
    • (2020)A survey of Twitter research: Data model, graph structure, sentiment analysis and attacksExpert Systems with Applications10.1016/j.eswa.2020.114006(114006)Online publication date: Sep-2020
    • (2017)DISCRN: A Distributed Storytelling Framework for Intelligence AnalysisBig Data10.1089/big.2017.00255:3(225-245)Online publication date: Sep-2017
    • (2015)Identifying vulnerable friends on a social networking site2015 12th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)10.1109/ICCWAMTIP.2015.7493954(94-101)Online publication date: Dec-2015
    • (2015)How Does Irony Affect Sentiment Analysis Tools?Progress in Artificial Intelligence10.1007/978-3-319-23485-4_81(803-808)Online publication date: 25-Aug-2015
    • (2014)Recommendation of OERs shared in social media based-on social networks analysis approach2014 IEEE Frontiers in Education Conference (FIE) Proceedings10.1109/FIE.2014.7044454(1-8)Online publication date: Oct-2014
    • (2013)The Evaluation of Online Social Network’s Nodes Influence Based on User’s Attribute and BehaviorFrontiers in Internet Technologies10.1007/978-3-642-53959-6_2(9-20)Online publication date: 2013

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