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Measuring the spreadability of users in microblogs |
Zhao-yun Ding, Yan Jia, Bin Zhou, Yi Han, Li He, Jian-feng Zhang |
College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China; School of Computer Science, National University of Defense Technology, Changsha 410073, China |
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Abstract Message forwarding (e.g., retweeting on Twitter.com) is one of the most popular functions in many existing microblogs, and a large number of users participate in the propagation of information, for any given messages. While this large number can generate notable diversity and not all users have the same ability to diffuse the messages, this also makes it challenging to find the true users with higher spreadability, those generally rated as interesting and authoritative to diffuse the messages. In this paper, a novel method called SpreadRank is proposed to measure the spreadability of users in microblogs, considering both the time interval of retweets and the location of users in information cascades. Experiments were conducted on a real dataset from Twitter containing about 0.26 million users and 10 million tweets, and the results showed that our method is consistently better than the PageRank method with the network of retweets and the method of retweetNum which measures the spreadability according to the number of retweets. Moreover, we find that a user with more tweets or followers does not always have stronger spreadability in microblogs.
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Received: 13 March 2013
Published: 05 September 2013
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Measuring the spreadability of users in microblogs
Message forwarding (e.g., retweeting on Twitter.com) is one of the most popular functions in many existing microblogs, and a large number of users participate in the propagation of information, for any given messages. While this large number can generate notable diversity and not all users have the same ability to diffuse the messages, this also makes it challenging to find the true users with higher spreadability, those generally rated as interesting and authoritative to diffuse the messages. In this paper, a novel method called SpreadRank is proposed to measure the spreadability of users in microblogs, considering both the time interval of retweets and the location of users in information cascades. Experiments were conducted on a real dataset from Twitter containing about 0.26 million users and 10 million tweets, and the results showed that our method is consistently better than the PageRank method with the network of retweets and the method of retweetNum which measures the spreadability according to the number of retweets. Moreover, we find that a user with more tweets or followers does not always have stronger spreadability in microblogs.
关键词:
Spreadability,
Influence,
PageRank,
Microblogs,
Social media,
Social network,
SpreadRank
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