Hoaxy

Abstract

Massive amounts of misinformation have been observed to spread in uncontrolled fashion across social media. Examples include rumors, hoaxes, fake news, and conspiracy theories. At the same time, several journalistic organizations devote significant efforts to high-quality fact checking of online claims. The resulting information cascades contain instances of both accurate and inaccurate information, unfold over multiple time scales, and often reach audiences of considerable size. All these factors pose challenges for the study of the social dynamics of online news sharing. Here we introduce Hoaxy, a platform for the collection, detection, and analysis of online misinformation and its related factchecking efforts. We discuss the design of the platform and present a preliminary analysis of a sample of public tweets containing both fake news and fact checking. We find that, in the aggregate, the sharing of fact-checking content typically lags that of misinformation by 10-20 hours. Moreover, fake news are dominated by very active users, while fact checking is a more grass-roots activity. With the increasing risks connected to massive online misinformation, social news observatories have the potential to help researchers, journalists, and the general public understand the dynamics of real and fake news sharing.

Investigating Italian disinformation spreading on Twitter in the context of 2019 European elections

“…Following a consolidated strategy [7,8,24], we leveraged Twitter Streaming API in order to collect tweets containing an explicit Uniform Resource Locator (URL) associated to news articles shared on a set of Italian disinformation websites. As a matter of fact, using the streaming endpoint allowed us to gather 100% of shared tweets matching the defined query (see next).…”

“…In accordance with current literature [6,[9][10][11]24] we use a "source-based" approach: we do not verify each news article manually but we assign the disinformation label to all items published on websites labeled as such (the same holds for fact-checking articles).…”

“…In this work we focus on the 5-month period preceding 2019 European elections; we pursue a consolidated setting, described in [8,24], for investigating the presence (and the impact) of disinformation in the Italian Twittersphere. We recognize that our analysis has a few inherent limitations: first, according to Reuters [17] Twitter is overtaken by far by other social platforms, accounting for only 8% of total users (with a decreasing trend) when it comes to consume news online compared to Instagram (13%), YouTube (25%), WhatsApp (27%) and Facebook (54%), which exhibit instead a rising trend.…”

Democracy, information, and libraries in a time of post-truth discourse

“…Some research on fact-checking suggests that devoting time and energy to checking facts and rebutting lies may be counterproductive since the rebuttals keep the disputed claims in the limelight (-Art of the lie‖, 2016). Fact-checking requires painstaking work, while disseminators of fake news are highly active and inevitably ahead (Shao et al, 2016). In light of the earlier discussion of empirical studies in social psychology and political science, one is tempted to question the practical value of the fact-checking activity.…”

Demographic factors and trust in different news sources

“…Each post in a timeline consisted of one scientific claim, and one of five hyperlink conditions: the control condition (no hyperlink), a hyperlink to an open-access scientific journal article which the scientific claim was based on, a hidden hyperlink that redirected to the same scientific journal article (Google, n.d.), a hyperlink to a mainstream media site (Flaxman, Goel, & Rao, 2016;Silverman, 2016), and a hyperlink to a fake news site (Shao, Ciampaglia, Flammini, & Menczer, 2016). For more details about the choice of scientific claims and news sources, and our operationalization of fake news, please see Verma et al (2017).…”