Social Determinants of Content Selection in the Age of (Mis)Information

Abstract

Abstract. Despite the enthusiastic rhetoric about the so called collective intelligence, conspiracy theories -e.g. global warming induced by chemtrails or the link between vaccines and autism -find on the Web a natural medium for their dissemination. Users preferentially consume information according to their system of beliefs and the strife within users of opposite narratives may result in heated debates. In this work we provide a genuine example of information consumption from a sample of 1.2 million of Facebook Italian users. We show by means of a thorough quantitative analysis that information supporting different worldviews -i.e. scientific and conspiracist news -are consumed in a comparable way by their respective users. Moreover, we measure the effect of the exposure to 4709 evidently false information (satirical version of conspiracy theses) and to 4502 debunking memes (information aiming at contrasting unsubstantiated rumors) of the most polarized users of conspiracy claims. We find that either contrasting or teasing consumers of conspiracy narratives increases their probability to interact again with unsubstantiated rumors.

Viral Misinformation

“…Conspiracists tend to reduce the complexity of reality by explaining significant social or political events as secret plots conceived by powerful individuals or organizations. Misinformation can be particularly di cult to correct [2,3]. Recently [4] it has been shown that conspiracist and mainstream information reverberate in a similar way on social media and that users generally exposed to conspiracy stories are more prone to like and share satirical information [5].…”

“…The resulting dataset contains 73 public Facebook pages; 34 of such pages are related to scientific news and the other 39 to news that can be considered conspiratorial; we refer to the former as science pages and to the latter as conspiracy pages. Notice that the dataset used in the analysis is the same used in [3] and [5]. In Table 1 we summarize the details of our data collection.…”

A model for the influence of media on the ideology of content in online social networks

“…The order parameters R 0 and R M allow us to quantify the impact of media nodes on content-spreading dynamics, where we note that one can also define timedependent analogs of (4) and (5). We define the media impact for one trial to be the ratio of the mean baseline ideological distance to the media-influenced ideological distance in that trial:…”

“…Individual user preferences play a strong role in the choice to consume news that conforms to (or even enhances) previously held views [4]. One reason that propaganda, misinformation, and disinformation has become so widespread on social media networks is that users are more likely to share a false or misleading story if it seems to confirm or support their biases [5,6]. Another challenge is that content is also spread and amplified through bot, cyborg, and sockpuppet accounts [7].…”

The Effect of Collective Attention on Controversial Debates on Social Media

“…To enrich this original dataset, we use the Twitter REST API to obtain all tweets of users who have participated in the discussion at least once. 6 Admittedly, this dataset might su er from sampling bias, however the topics are speci c enough that the distortion should be negligible [28]. There might also be recency bias due to the addition of the latest tweets of the users.…”