Information Diffusion and Provenance of Interactions in Twitter: Is it only about Retweets?

Io Taxidou, Peter M. Fischer, Tom De Nies, Erik Mannens, Rik Van de Walle

Abstract: This paper sheds light on the different interaction types among social media users that benefit information diffusion and provenance analysis. In particular, we identify explicit and implicit interactions in Twitter, including informal conventions applied by users. In our empirical evaluation considering only retweets, the most common means of information propagation in Twitter, we can infer 50% of message provenance. However, if we consider other types of interactions, we can explain another 13%. Accordingly, we enrich the PROV-SAID model for information diffusion, which extends the W3C PROV standard for provenance.