Name
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. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1631/jzus.CIIP1302 | Journal of Zhejiang University SCIENCE C |
Keywords | Field | DocType |
Spreadability, Influence, PageRank, Microblogs, Social media, Social network, SpreadRank, TP391 | Message forwarding,PageRank,World Wide Web,Social media,Social network,Computer science,Spreadability,Information cascade,Microblogging | Journal |
Volume | Issue | ISSN |
14 | 9 | 1869-196X |
Citations | PageRank | References |
3 | 0.39 | 20 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhaoyun Ding | 1 | 29 | 5.90 |
| Yan Jia | 2 | 56 | 10.52 |
| Bin Zhou | 3 | 71 | 9.48 |
| Yi Han | 4 | 93 | 8.94 |
| Li He | 5 | 4 | 1.09 |
| jianfeng zhang | 6 | 3 | 0.39 |