Promoting engagement with social fact-checks online: Investigating the roles of social connection and shared partisanship

TL;DR

This study explores how social connections and shared political views affect how people respond to corrections on social media.

Contribution

The study introduces a field experiment using bots to test how partisanship and social connections influence correction engagement.

Findings

Social connection increased engagement with corrections from co-partisans.

People feel more obligated to respond to those who follow them, even outside misinformation contexts.

Shared partisanship had no significant effect without social connections.

Abstract

Social corrections – where users correct each other – can help rectify inaccurate beliefs. However, social corrections are often ignored. Here we ask under what conditions social corrections promote engagement from corrected users, allowing for greater insight into how users respond to debunking messages (even if such responses are negative). Prior work suggests two key factors may help promote engagement with corrections – partisan alignment between users, and social connections between users. We investigate these factors here. First, we conducted a field experiment on Twitter (X) using human-looking bots to examine how shared partisanship and prior social connection affect correction engagement. We randomized whether our accounts identified as Democrat or Republican, and whether they followed Twitter users and liked three of their tweets before correcting them (creating a minimal social connection). We found that shared partisanship had no significant effect in the baseline (no social connection) condition. Interestingly, social connection increased engagement with corrections from co-partisans. Effects in the social counter-partisan condition were ambiguous. Follow-up survey experiments largely replicated these results and found evidence for a generalized norm of responding, wherein people feel more obligated to respond to people who follow them – even outside the context of misinformation correction. Our findings have important implications for increasing engagement with social corrections online.

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