Name
Abstract | ||
|---|---|---|
Social networks are intensively and extensively used to exchange news and contents in real time. The lack of a global authority for assessing posts truthfulness however allows malicious to exhibit unfair behaviours; identifying methodologies to detect hoaxes and defamatory content automatically is therefore more and more required. Social networks as Facebook and Twitter provided specific solutions and general approaches were also developed; in this paper we present a general model that takes into account both post as well as users' credibility, using a duplex network of acquaintances and credibility among users. First experiments show that it is possible to distinguish individuals who post non-truthful content through a combined analysis of both the news content and the reposts they get from their contacts. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-66379-1_14 | Studies in Computational Intelligence |
Keywords | Field | DocType |
Credibility,Social network,Social contagion | Emotional contagion,Internet privacy,Social network,Credibility,Computer science | Conference |
Volume | ISSN | Citations |
737.0 | 1860-949X | 1 |
PageRank | References | Authors |
0.36 | 10 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincenza Carchiolo | 1 | 261 | 51.62 |
| Alessandro Longheu | 2 | 142 | 29.98 |
| Michele Malgeri | 3 | 219 | 42.79 |
| Giuseppe Mangioni | 4 | 199 | 37.16 |
| M. Previti | 5 | 1 | 0.36 |