The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter
This addresses the problem of understanding message propagation on social media for researchers and practitioners, but it is incremental as it builds on prior work by isolating wording effects.
The study investigated whether the wording of a tweet affects its retweet rate, controlling for author and topic by analyzing pairs of tweets with the same URL from the same user. The result showed that computational methods developed in the research outperformed both average humans and a strong baseline in predicting which version attracted more retweets.
Consider a person trying to spread an important message on a social network. He/she can spend hours trying to craft the message. Does it actually matter? While there has been extensive prior work looking into predicting popularity of social-media content, the effect of wording per se has rarely been studied since it is often confounded with the popularity of the author and the topic. To control for these confounding factors, we take advantage of the surprising fact that there are many pairs of tweets containing the same url and written by the same user but employing different wording. Given such pairs, we ask: which version attracts more retweets? This turns out to be a more difficult task than predicting popular topics. Still, humans can answer this question better than chance (but far from perfectly), and the computational methods we develop can do better than both an average human and a strong competing method trained on non-controlled data.