Torky, Mohamed, Baberse, Ramadan, Ibrahim, Ragia, Hassanien, Aboul Ella, Schaefer, Gerald, Korovin, Iakov and Zhu, Shao Ying (2016) Credibility investigation of newsworthy tweets using a visualising Petri net model. In: 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 003894-003898

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Abstract

Investigating information credibility is an important problem in online social networks such as Twitter. Since misleading information can get easily propagated in Twitter, ranking tweets according to their credibility can help to detect rumors and identify misinformation. In this paper, we propose a Petri net model to visualise tweet credibility in Twitter. We consider the uniform resource locator (URL) as an effective feature in evaluating tweet credibility since it is used to identify the source of tweets, especially for newsworthy tweets. We perform an experimental evaluation on about 1000 tweets, and show that the proposed model is effective for assigning tweets to two classes: credible and incredible tweets, which each class being further divided into two sub-classes (“credible” and “seem credible” and “doubtful” and “incredible” tweets, respectively) based on appropriate features.

Item Type:	Book Section
Status:	Published
DOI:	10.1109/SMC.2016.7844842
School/Department:	School of Science, Technology and Health
URI:	https://ray.yorksj.ac.uk/id/eprint/9969

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