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| Content Provider | ACM Digital Library |
|---|---|
| Author | Bild, David R. Dick, Robert P. Wallach, Dan S. Liu, Yue Mao, Z. Morley |
| Copyright Year | 2015 |
| Abstract | Most previous analysis of Twitter user behavior has focused on individual information cascades and the social followers graph, in which the nodes for two users are connected if one follows the other. We instead study aggregate user behavior and the retweet graph with a focus on quantitative descriptions. We find that the lifetime tweet distribution is a type-II discrete Weibull stemming from a power law hazard function, that the tweet rate distribution, although asymptotically power law, exhibits a lognormal cutoff over finite sample intervals, and that the inter-tweet interval distribution is a power law with exponential cutoff. The retweet graph is small-world and scale-free, like the social graph, but less disassortative and has much stronger clustering. These differences are consistent with it better capturing the real-world social relationships of and trust between users than the social graph. Beyond just understanding and modeling human communication patterns and social networks, applications for alternative, decentralized microblogging systems---both predicting real-word performance and detecting spam---are discussed. |
| Starting Page | 1 |
| Ending Page | 24 |
| Page Count | 24 |
| File Format | |
| ISSN | 15335399 |
| e-ISSN | 15576051 |
| DOI | 10.1145/2700060 |
| Volume Number | 15 |
| Issue Number | 1 |
| Journal | ACM Transactions on Internet Technology (TOIT) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-03-12 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Social network analysis Decentralized network architectures Microblogging systems |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Networks and Communications |
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