Name
Abstract | ||
|---|---|---|
Twitter is a crucial platform to get access to breaking news and timely information. However, due to questionable provenance, uncontrollable broadcasting, and unstructured languages in tweets, Twitter is hardly a trustworthy source of breaking news. In this paper, we propose a novel topic-focused trust model to assess trustworthiness of users and tweets in Twitter. Unlike traditional graph-based trust ranking approaches in the literature, our method is scalable and can consider heterogeneous contextual properties to rate topic-focused tweets and users. We demonstrate the effectiveness of our topic-focused trustworthiness estimation method with extensive experiments using real Twitter data in Latin America. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1016/j.comcom.2015.08.001 | Computer Communications |
Keywords | Field | DocType |
Trust management,Social networks,Twitter,Trustworthiness,Credibility | Broadcasting,Graph,World Wide Web,Social network,Ranking,Credibility,Computer science,Trustworthiness,Scalability | Journal |
Volume | ISSN | Citations |
76 | 0140-3664 | 12 |
PageRank | References | Authors |
0.56 | 32 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liang Zhao | 1 | 386 | 54.50 |
| Ting Hua | 2 | 102 | 5.59 |
| Chang-Tien Lu | 3 | 1097 | 115.77 |
| Ing-Ray Chen | 4 | 1769 | 157.86 |