The theater of fake news spreading, who plays which role? A study on real graphs of spreading on Twitter

During the battle between fake news and truth in Twitter, users of each side take different roles such as tweeting the original content or retweeting the published content, while some of them act as super spreaders and beget successive circles of diffusion, and some just end up as unwelcome spreaders who emerge and die out before having any impact. This study seeks to understand how these actors differ from each other based on their characteristics, interconnections and cascading the flow. To this aim, we crawl 5 fake news stories out of Twitter along with the underlying graphs of diffusion, with an overall number of 8 M nodes and 28 M links. Then, we peer into these graphs, visualize them and analyze the diffusion process. The findings reveal that tweeters of truth have the highest value of page rank centrality while fake news retweeters are superior in rate of modularity and ratio of intra- to inter-links. In addition, it turns out that reciprocal relationships are the channels of diffusion into the network, however, to spark the spreading process itself, users who are freer from the reciprocal ties with lower ratio of following to follower act better. Furthermore, counterintuitively, the data analysis shows that having more antecedent spreaders leads to the larger time lag of spreading from the retweeters. The findings will be discussed in the light of social theories and contribute to practical strategies against fake news spreading on online social media.