Name
Abstract | ||
|---|---|---|
In recent years, social media has changed the way we interact and communicate. Although the existing structure of social media allows users to easily create, receive, and propagate pieces of information, many a time, users do not have background knowledge about the received information, including the provenance (sources or originators) of information, and other recipients who may have retransmitted or modified the information. Providing such additional context to the received information can help users know how much value, trust, and validity should be placed in received information. To judge the credibility of the received piece of information, it is vital to know who are its sources, and how information propagates from sources to other social media users. In this paper, we are studying a novel research problem that facilitates a few known recipients to recover other unknown recipients, and seek the provenance of information. The experimental results with Facebook and Twitter datasets show that the proposed algorithm is effective in correctly recovering the unknown recipients and seeking the provenance of information. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2492517.2492629 | ASONAM |
Keywords | Field | DocType |
existing structure,social media user,information propagates,social media,additional context,information recipient,unknown recipient,twitter datasets show,known recipient,privacy | Data mining,Internet privacy,World Wide Web,Social media,Know-how,Credibility,Computer science | Conference |
Citations | PageRank | References |
6 | 0.64 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhuo Feng | 1 | 463 | 40.15 |
| Pritam Gundecha | 2 | 81 | 6.41 |
| Huan Liu | 3 | 12695 | 741.34 |