Engaging Politically Diverse Audiences on Social Media

TL;DR

This paper analyzes how political polarization influences social media engagement, developing a model to help journalists craft tweets that appeal to diverse audiences, and validating it through real-world Twitter experiments.

Contribution

It introduces a novel model linking tweet content to audience political diversity and demonstrates its effectiveness in engaging diverse Twitter users through experimental validation.

Findings

Model successfully predicts politically diverse engagement in most experiments

Tweets optimized by the model attract more diverse audiences

Real-world Twitter experiments confirm the model's practical utility

Abstract

We study how political polarization is reflected in the social media posts used by media outlets to promote their content online. In particular, we track the Twitter posts of several media outlets over the course of more than three years (566K tweets), and the engagement with these tweets from other users (104M retweets), modeling the relationship between the tweet text and the political diversity of the audience. We build a tool that integrates our model and helps journalists craft tweets that are engaging to a politically diverse audience, guided by the model predictions. To test the real-world impact of the tool, we partner with the PBS documentary series Frontline and run a series of advertising experiments on Twitter. We find that in seven out of the ten experiments, the tweets selected by our model were indeed engaging to a more politically diverse audience, illustrating the effectiveness of our approach.