Date Published: April 27, 2018
Publisher: Public Library of Science
Author(s): Chengcheng Shao, Pik-Mai Hui, Lei Wang, Xinwen Jiang, Alessandro Flammini, Filippo Menczer, Giovanni Luca Ciampaglia, Alain Barrat.
Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy captures public tweets that include links to articles from low-credibility and fact-checking sources. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network.
The viral spread of online misinformation is emerging as a major threat to the free exchange of opinions, and consequently to democracy. Recent Pew Research Center surveys found that 63% of Americans do not trust the news coming from social media, even though an increasing majority of respondents uses social media to get the news on a regular basis (67% in 2017, up from 62% in 2016). Even more disturbing, 64% of Americans say that fake news have left them with a great deal of confusion about current events, and 23% also admit to passing on fake news stories to their social media contacts, either intentionally or unintentionally [1, 2, 3].
Having described in the prior section how Hoaxy collects data, let us now analyze the misinformation diffusion networks. To the best of our knowledge, the following is the first in-depth analysis of the diffusion network of online misinformation and fact-checking in the period of the 2016 US Presidential Election.
The rise of digital misinformation is calling into question the integrity of our information ecosystem. Here we made two contributions to the ongoing debate on how to best combat this threat. First, we presented Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. We described key aspects of its design and implementation. All Hoaxy data is available through an open API. Second, using data from Hoaxy, we presented an in-depth analysis of the misinformation diffusion network in the run up to and wake of the 2016 US Presidential Election. We found that the network is strongly segregated along the two types of information circulating in it, and that a dense, stable core emerged after the election. We characterized the main core in terms of multiple centrality measures and proposed an efficient strategies to reduce the circulation of information by penalizing key nodes in this network. The networks used in the present analysis are available on an institutional repository (see Methods).