How Humans versus Bots React to Deceptive and Trusted News Sources: A Case Study of Active Users

TL;DR

This study compares how humans and bots react to news sources of varying credibility on social media, revealing differences in reaction speed, content, and participation levels, with implications for misinformation spread.

Contribution

It provides a detailed analysis of bot and human responses to credible and non-credible news sources, highlighting behavioral differences and reaction dynamics.

Findings

Bots account for 9-15% of reactions but only 7-10% of accounts.

Trusted sources elicit more human reactions.

Bots respond faster than humans to propaganda sources.

Abstract

Society's reliance on social media as a primary source of news has spawned a renewed focus on the spread of misinformation. In this work, we identify the differences in how social media accounts identified as bots react to news sources of varying credibility, regardless of the veracity of the content those sources have shared. We analyze bot and human responses annotated using a fine-grained model that labels responses as being an answer, appreciation, agreement, disagreement, an elaboration, humor, or a negative reaction. We present key findings of our analysis into the prevalence of bots, the variety and speed of bot and human reactions, and the disparity in authorship of reaction tweets between these two sub-populations. We observe that bots are responsible for 9-15% of the reactions to sources of any given type but comprise only 7-10% of accounts responsible for reaction-tweets; trusted news sources have the highest proportion of humans who reacted; bots respond with significantly shorter delays than humans when posting answer-reactions in response to sources identified as propaganda. Finally, we report significantly different inequality levels in reaction rates for accounts identified as bots vs not.