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...ts could propagate multiple hops away from the source before they are retweeted throughout the network. Furthermore, because of the tight connection between users as suggested in the triadic closure (=-=Granovetter 1973-=-), retweeting in a social network can serve as a powerful tool to reinforce a message—for instance, the probability of adopting an innovation increases when not one but a group of users repeat the sam...

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...res such as indegree alone reveals very little about the influence of a user. Introduction Influence has long been studied in the fields of sociology, communication, marketing, and political science (=-=Rogers 1962-=-; Katz and Lazarsfeld 1955). The notion of influence plays a vital role in how businesses operate and how a society functions—for instance, see observations on how fashion spreads (Gladwell 2002) and ...

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...ead, it posits that the key factors determining influence are (i) the interpersonal relationship among ordinary users and (ii) the readiness of a society to adopt an innovation (Watts and Dodds 2007; =-=Domingos and Richardson 2001-=-). This modern view of influence leads to marketing strategies such as collaborative filtering. These theories, however, are still just theories, because there has been a lack of empirical data that c...

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...tal volume of tweets merely increased over time. Hence, if we didn’t normalize the results, the trend wouldn’t be interesting. Google similarly normalizes the data when analyzing their search trends (=-=Ginsberg et al. 2009-=-). Figure 4 displays the time evolution of the normalized retweets and mentions of the 233 all-time influential users.0.0015 0.004 Retweet probability, P 0.0012 0.0009 0.0006 0.0003 Top 10 users Top ...

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...ndegree alone reveals very little about the influence of a user. Introduction Influence has long been studied in the fields of sociology, communication, marketing, and political science (Rogers 1962; =-=Katz and Lazarsfeld 1955-=-). The notion of influence plays a vital role in how businesses operate and how a society functions—for instance, see observations on how fashion spreads (Gladwell 2002) and how people vote (Berry and...

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...en made to track influence on Twitter. The Web Ecology Project tracked 12 popular Twitter users for a 10-day period and grouped a user’s influence into two types: conversation-based and contentbased (=-=Leavitt et al. 2009-=-). This work concluded that news media are better at spreading content, while celebrities are better at simply making conversation. Our work extends their notion of influence and uses extensive data t...

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...ure, so that the rank of 1 indicates the most influential user and increasing rank indicates a less influential user. Users with the same influence value receive the average of the rank amongst them (=-=Buck 1980-=-). Once every user is assigned a rank for each influence measure, we are ready to quantify how a user’s rank varies across different measures and examine what kinds of users are ranked high for a give...

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...ceptually a single interaction domain for users. Because it is hard to determine influence of users who have few tweets, we borrowed the concept of “active users” from the traditional media research (=-=Levy and Windhal 1985-=-) and focused on those users with some minimum level of activity. We ignored users who had posted fewer than 10 tweets during their entire lifetime. We also ignored users for whom we did not have a va...