Abstract
Millions of posts are being generated in real-time by users in social networking services, such as Twitter. However, a considerable number of those posts are mundane posts that are of interest to the authors and possibly their friends only. This paper investigates the problem of automatically discovering valuable posts that may be of potential interest to a wider audience. Specifically, we model the structure of Twitter as a graph consisting of users and posts as nodes and retweet relations between the nodes as edges. We propose a variant of the HITS algorithm for producing a static ranking of posts. Experimental results on real world data demonstrate that our method can achieve better performance than several baseline methods.
Original language | English |
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Title of host publication | SIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval |
Pages | 1073-1074 |
Number of pages | 2 |
DOIs | |
Publication status | Published - 2012 |
Event | 35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012 - Portland, OR, United States Duration: 2012 Aug 12 → 2012 Aug 16 |
Publication series
Name | SIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval |
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Other
Other | 35th Annual ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2012 |
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Country | United States |
City | Portland, OR |
Period | 12/8/12 → 12/8/16 |
Keywords
- hits
- social network
- tweet ranking
ASJC Scopus subject areas
- Information Systems