Mapping social dynamics on Facebook: The Brexit debate

Abstract

Nowadays users get informed and shape their opinion through social media. However, the disintermediated access to contents does not guarantee quality of information. Selective exposure and confirmation bias, indeed, have been shown to play a pivotal role in content consumption and information spreading. Users tend to select information adhering (and reinforcing) their worldview and to ignore dissenting information. This pattern elicits the formation of polarized groups – i.e., echo chambers – where the interaction with like-minded people might even reinforce polarization. In this work we address news consumption around Brexit in UK on Facebook. In particular, we perform a massive analysis on more than 1 million users interacting with Brexit related posts from the main news providers between January and July 2016. We show that consumption patterns elicit the emergence of two distinct communities of news outlets. Furthermore, to better characterize inner group dynamics, we introduce a new technique which combines automatic topic extraction and sentiment analysis. We compare how the same topics are presented on posts and the related emotional response on comments finding significant differences in both echo chambers and that polarization influences the perception of topics. Our results provide important insights about the determinants of polarization and evolution of core narratives on online debating

Dealing with digital misinformation: a polarised context of narratives and tribes

“…To better frame the main determinants behind content consumption and the emergence of collective narratives on online social media, in this section we will focus on the discussion around two of the most recent and debated topics: Brexit (Del Vicario et al., ) and vaccines (Schmidt et al., ).…”

“…To characterise users’ behaviour on Facebook pages engaged in the debate around Brexit, we first analysed their interaction patterns with the pages (Del Vicario et al., ). To this aim, we built the page‐users graph (Figure ), in which nodes along the ring are pages, and two pages are connected by an edge if at least one user liked a post from each of them.…”

“…As anticipated, our approach takes advantage of both the question‐framing capabilities of social sciences and the experimental and quantitative tools of hard sciences. In this section, we present a collection of data sets (Bessi et al., , ; Zollo et al., , ; Del Vicario et al., , ; Schmidt et al., , ) that lay the groundwork for our analysis.…”

“…Following the Europe Media Monitor (EMM) list (Steinberger et al., ), we selected all news outlets (and their related Facebook page) whose legal head office (at least one of them) was located in the United Kingdom (Del Vicario et al., ). For each page, we downloaded all the posts from 1 January to 15 July 2016, as well as all the related likes and comments.…”

“… Communities were detected using the Fast Greedy (FG) algorithm. For more details please refer to (Del Vicario et al., ). …”