Paper “Measuring user engagement with low credibility media sources in a controversial online debate“, just published on EPJ Data Science, follows up our previous research on studying immigration as a divisive topic on Twitter. We extended the studying trying to capture how such arguments have been manipulated by means of accounts showing bot-like activities and the spread of information from low crediblity sources. This is the product of a joint effort between Salvatore Vilella, Alfonso Semeraro, Giancarlo Ruffo (University of Turin), and Daniela Paolotti (ISI Foundation).
We quantify social media user engagement with low-credibility online news media sources using a simple and intuitive methodology, that we showcase with an empirical case study of the Twitter debate on immigration in Italy. By assigning the Twitter users an Untrustworthiness (U) score based on how frequently they engage with unreliable media outlets and cross-checking it with a qualitative political annotation of the communities, we show that such information consumption is not equally distributed across the Twitter users. Indeed, we identify clusters characterised by a very high presence of accounts that frequently share content from less reliable news sources. The users with high U are more keen to interact with bot-like accounts that tend to inject more unreliable content into the network and to retweet that content. Thus, our methodology applied to this real-world network provides evidence, in an easy and straightforward way, that there is strong interplay between accounts that display higher bot-like activity and users more focused on news from unreliable sources and that this influences the diffusion of this information across the network.