Using Plutchik’s wheel of emotions framework, we identify the emotional content of 133,487 social media posts and the audience’s emotional engagement expressed in 2,824,162 comments on those posts. We measure nine emotions (anger, anticipation, anxiety, disgust, joy, fear, sadness, surprise, trust) and two sentiments (positive and negative) using two extraction resources (EmoLex, LIWC) for eight major news outlets across four social media platforms (Facebook, Instagram, Twitter, and YouTube) during eight months.
We then apply two approaches (Logistic Regression, Long Short-Term Memory) to predict emotional audience reactions before and after publishing the posts.
Findings show significant differences for positive emotions but not for negative in the comments among the platforms. F1-scores for predicting emotional audience engagement are more than 70% for some emotions for some news outlets. Implications are that news outlets have leverage in steering emotional engagement for posts on social media platforms.
The findings have theoretical and practical implications for understanding the complex emotional and informational interplay among social media content, platforms, and audiences.
Aldous, K, An, J, and Jansen, B. J.(2022) Measuring 9 emotions of news posts from 8 news organizations across 4 social media platforms for 8 months. ACM Transactions on Social Computing. 4(4), Article 15.