Leila Weitzel
José Palazzo M. de Oliveira
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.
- Albert, R. and Barabási, A. L. 2002. Statistical mechanics of complex networks. Reviews of modern physics. 74, 1 (2002), 47.Google Scholar
- Balkundi, P. and Kilduff, M. 2005. The ties that lead: A social network approach to leadership. The Leadership Quarterly. 16, 6 (Dec. 2005), 941--961.Google ScholarCross Ref
- Blar-Ilan, J. and Peritz, B. C. 2009. A method for measuring the evolution of a topic on the Web: The case of "informetrics." Journal of the American Society for Information Science and Technology. 60, 9 (2009), 1730--1740. Google ScholarDigital Library
- Bonacich, P. 2007. Some unique properties of eigenvector centrality. Social Networks. 29, 4 (Oct. 2007), 555--564.Google ScholarCross Ref
- Bongwon Suh et al. 2010. Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network. Social Computing (SocialCom), 2010 IEEE Second International Conference on (2010), 177--184. Google ScholarDigital Library
- Boyd, D. et al. 2010. Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter. Hawaii International Conference on System Sciences (Los Alamitos, CA, USA, 2010), 1--10. Google ScholarDigital Library
- Cha, M. et al. 2010. Measuring User Influence in Twitter: The Million Follower Fallacy. International Conference on Weblogs and Social Media (2010).Google Scholar
- Detecting Important Nodes to Community Structure Using the Spectrum of the Graph: 2010. http://arxiv.org/abs/1101.1703. Accessed: 2011-03-31.Google Scholar
- Gayo-Avello, D. 2010. Nepotistic relationships in twitter and their impact on rank prestige algorithms. Arxiv preprint arXiv:1004.0816. (2010).Google Scholar
- Girvan, M. 2002. Community structure in social and biological networks. Proceedings of the National Academy of Sciences. 99, 12 (Jun. 2002), 7821--7826.Google ScholarCross Ref
- Gruhl, D. et al. 2004. Information diffusion through blogspace. Proceedings of the 13th international conference on World Wide Web (New York, NY, USA, 2004), 491--501. Google ScholarDigital Library
- Hansen, D. et al. 2011. Analyzing Social Media Networks with NodeXL: Insights from a Connected World. Morgan Kaufmann. Google ScholarDigital Library
- How to Become Famous in the Microblog World: 2010. http://www.aaai.org/ocs/index.php/ICWSM/ICWSM10/paper/view/1505/1887.Google Scholar
- Kim, W. et al. 2010. On social Web sites. Information Systems. 35, 2 (Apr. 2010), 215--236. Google ScholarDigital Library
- Kwak, H. et al. 2010. What is Twitter, a social network or a news media? Proceedings of the 19th international conference on World wide web (Raleigh, North Carolina, USA, 2010), 591--600. Google ScholarDigital Library
- McPherson, M. et al. 2001. Birds of a feather: Homophily in social networks. Annual review of sociology. 27, (2001), 415--444.Google Scholar
- Nagarajan, M. et al. 2010. A Qualitative Examination of Topical Tweet and Retweet Practices. ICWSM 2010 (Washington, DC, 2010).Google Scholar
- Nagle, F. and Singh, L. 2009. Can Friends Be Trusted? Exploring Privacy in Online Social Networks. 2009 International Conference on Advances in Social Network Analysis and Mining (Athens, Greece, Jul. 2009), 312--315. Google ScholarDigital Library
- NodeXL: a free and open network overview, discovery and exploration add-in for Excel: 2007. http://www.smrfoundation.org. Accessed: 2011-05-19.Google Scholar
- Page, L. et al. 1999. The PageRank Citation Ranking: Bringing Order to the Web. Stanford InfoLab.Google Scholar
- Pal, A. and Counts, S. 2011. Identifying topical authorities in microblogs. Proceedings of the fourth ACM international conference on Web search and data mining (Hong Kong, China, 2011), 45--54. Google ScholarDigital Library
- Rijsbergen, C. J. van 1979. Information retrieval. Butterworths. Google ScholarDigital Library
- Romero, D. M. et al. 2011. Influence and passivity in social media. Proceedings of the 20th international conference companion on World wide web - WWW '11 (Hyderabad, India, 2011), 113. Google ScholarDigital Library
- Sousa, D. et al. 2010. Characterization of the twitter @replies network. Proceedings of the 2nd international workshop on Search and mining user-generated contents - SMUC '10 (Toronto, ON, Canada, 2010), 63. Google ScholarDigital Library
- Wang, Y. and Liu, Z. 2007. Automatic detecting indicators for quality of health information on the Web. International Journal of Medical Informatics. 76, 8 (Aug. 2007), 575--582.Google ScholarCross Ref
- Wasserman, S. 1999. Social network analysis?: methods and applications. Cambridge University Press.Google Scholar
- Welch, M. J. et al. 2011. Topical semantics of twitter links. Proceedings of the fourth ACM international conference on Web search and data mining (Hong Kong, China, 2011), 327--336. Google ScholarDigital Library
- Yamaguchi, Y. et al. 2010. TURank: Twitter User Ranking Based on User-Tweet Graph Analysis. Web Information Systems Engineering -- WISE 2010. Springer Berlin/Heidelberg. 240--253. Google ScholarDigital Library
- Ye, S. and Wu, S. 2010. Measuring Message Propagation and Social Influence on Twitter.com. Social Informatics. Springer Berlin/Heidelberg. 216--231. Google ScholarDigital Library
Index Terms
- Measuring node importance on Twitter microblogging
Recommendations
What is Twitter, a social network or a news media?
WWW '10: Proceedings of the 19th international conference on World wide webTwitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal ...
Measuring influence on Twitter
i-KNOW '11: Proceedings of the 11th International Conference on Knowledge Management and Knowledge TechnologiesThere are currently over 175 million Twitter accounts worldwide, making Twitter one of the most popular and most observed Social Media platform. But Twitter is not so much a social network where the exchange of personal information is facilitated -- in ...
Measuring and Detecting Virality on Social Media: The Case of Twitter’s Viral Tweets Topic
WWW '23 Companion: Companion Proceedings of the ACM Web Conference 2023Social media posts may go viral and reach large numbers of people within a short period of time. Such posts may threaten the public dialogue if they contain misleading content, making their early detection highly crucial. Previous works proposed their ...
Comments