How does fake news spread? Understanding pathways of disinformation spread through APIs

TL;DR

This paper investigates how social media APIs facilitate disinformation spread by analyzing API usage patterns, developing a four-stage framework, and examining the 2016 US elections to inform policy recommendations.

Contribution

It introduces a novel four-stage framework for understanding disinformation pathways via social media APIs, based on extensive analysis of code repositories and real-world events.

Findings

Identification of official and unofficial API usage patterns

Development of a four-stage disinformation spread framework

Insights from the 2016 US Elections case study

Abstract

What are the pathways for spreading disinformation on social media platforms? This article addresses this question by collecting, categorising, and situating an extensive body of research on how application programming interfaces (APIs) provided by social media platforms facilitate the spread of disinformation. We first examine the landscape of official social media APIs, then perform quantitative research on the open-source code repositories GitHub and GitLab to understand the usage patterns of these APIs. By inspecting the code repositories, we classify developers' usage of the APIs as official and unofficial, and further develop a four-stage framework characterising pathways for spreading disinformation on social media platforms. We further highlight how the stages in the framework were activated during the 2016 US Presidential Elections, before providing policy recommendations for issues relating to access to APIs, algorithmic content, advertisements, and suggest rapid response to coordinate campaigns, development of collaborative, and participatory approaches as well as government stewardship in the regulation of social media platforms.