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| − | This a [[Category::Paper]] discussed in Social Media Analysis 10-802 in Spring 2010.
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| − | == Citation ==
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| − | Measuring user influence in twitter: The million follower fallacy,
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| − | Cha, M. and Haddadi, H. and Benevenuto, F. and Gummadi, K.P., ICWSM 2010
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| − | == Online version ==
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| − | [http://snap.stanford.edu/class/cs224w-readings/cha10influence.pdf Measuring User Influence in Twitter: The Million Follower Fallacy
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| − | == Summary ==
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| − | This paper characterize influence of a user in social media. A more influential user causes others who are connected with him to act in a certain way. We can use information about influence in some practical applications such as viral marketing.
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| − | Three different measures for influence are defined in the paper.
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| − | Twitter data collected for 54M users is used for experiment. Total number of follow links present in the dataset is 1,963,263,821. Dataset has 1,755,925,520 number of tweets.
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| − | Three different measures of influence used are:
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| − | 1. Indegree: Total number of followers. Essentially it computes how many people at most read tweets of a particular twitter.
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| − | 2. Mention: Number of mentions for a twitter. This reflects how many people has listened to a tweeter and mentioned him/her in their tweets.
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| − | 3. Retweets: Number of retweets for a specific user.
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| − | Authors also investigate in the paper whether the influence of a user hold across all topics or it is topic specific?
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| − | == Findings ==
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| − | Influence computed using above measures is then compared using Spearman’s rank correlation[http://en.wikipedia.org/wiki/Spearman's_rank_correlation_coefficient]
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| − | Correlation between measures is as following:
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| − | Indegree vs retweets: .549
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| − | Indegree vs mentions: .638
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| − | Retweets vs mentions: .580
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| − | This shows that there is stronger correlation between Indegree and mentions.
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| − | To compute influence for a particular topic, they choose tweets related to three famous topics of 2009. These topics are the Iranian presidential election, the outbreak of the H1N1 influenza, and the death of Michael Jackson. Among the users who tweeted about these topics, there were 13,219 users who tweeted about all three topics.
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| − | They found that most influential users hold significant influence across topics.
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| − | == Related papers ==
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| − | * Learning Influence Probabilities In Social Networks. Goyal, A.; Bonchi, F.; and Lakshmanan, L. V. S. 2010.[http://www.cs.ubc.ca/~goyal/research/wsdm339-goyal.pdf]
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| − | * The Dynamics of Viral Marketing. Leskovec, J.; Adamic, L. A.; and Huberman, B. A. 2007.ACM Trans. on the Web (TWEB)[http://cs.stanford.edu/people/jure/pubs/viral-tweb.pdf]
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