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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 ofsocial-media content, the effect of wording per se has rarely been studiedsince it is often confounded with the popularity of the author and the topic.To control for these confounding factors, we take advantage of the surprisingfact that there are many pairs of tweets containing the same url and written bythe same user but employing different wording. Given such pairs, we ask: whichversion attracts more retweets? This turns out to be a more difficult task thanpredicting popular topics. Still, humans can answer this question better thanchance (but far from perfectly), and the computational methods we develop cando better than both an average human and a strong competing method trained onnon-controlled data.

The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter