Science vs conspiracy: collective narratives in the age of misinformation

Abstract

The large availability of user provided contents on online social media facilitates people aggregation around shared beliefs, interests, worldviews and narratives. In spite of the enthusiastic rhetoric about the so called collective intelligence unsubstantiated rumors and conspiracy theories-e.g., chemtrails, reptilians or the Illuminati-are pervasive in online social networks (OSN). In this work we study, on a sample of 1.2 million of individuals, how information related to very distinct narratives-i.e. main stream scientific and conspiracy news-are consumed and shape communities on Facebook. Our results show that polarized communities emerge around distinct types of contents and usual consumers of conspiracy news result to be more focused and self-contained on their specific contents. To test potential biases induced by the continued exposure to unsubstantiated rumors on users' content selection, we conclude our analysis measuring how users respond to 4,709 troll information-i.e. parodistic and sarcastic imitation of conspiracy theories. We find that 77.92% of likes and 80.86% of comments are from users usually interacting with conspiracy stories.

Fig 1. Users Activity.

Empirical complementary cumulative distribution function (CCDF) of users’ activity (like, comment and share) for post grouped by page category. The distributions are indicating heavy–tailed consumption patterns for the various pages.

Fig 2. Post lifetime.

Empirical complementary cumulative distribution function (CCDF), grouped by page category, of the temporal distance between the first and last comment to each post. The life time of posts in both categories is similar.

Fig 3. Page Network.

The membership of 73 pages as a) identified by means of their self-description, b) by applying the multi-level modularity optimization algorithm, and c) by looking at the maximum modularity score. Community detection algorithms based on modularity are good discriminants for community partitioning.

Fig 4. Consumption patterns of polarized users.

Empirical complementary cumulative distribution function (CCDF) for likes and comments of polarized users.

Fig 5. Activity and communities.

Posts on which at least a member of each the two communities has commented. The number of posts is 7,751 (1,991 from scientific news and 5,760 from conspiracy news). Here we show the commenting activity in terms of polarized users on the two categories.

Fig 6. Polarized users on false information.

Percentage of comments and likes on intentional false memes posted by a satirical page from polarized users of the two categories.

Fig 7. Polarized users and activity.

Number of polarized users as a function of the thresholding value θ on the two categories.