Bad News Travelled Slow on Twitter

What is it about?

In October of 2018, Twitter released its first dataset of all of the known fake Twitter accounts created by Iranian and Russian operatives. The large data corpus has roughly 4,000 accounts, over 10 million tweets, as well as the statistics on the popularity of each tweet (e.g., the number of retweets and likes). The dataset was analyzed with two research questions in mind 1) what emotional tones were the most common in the fake tweets and 2) whether they succeeded in engaging users. According to the saying that “bad news travels fast,” it is understandable that troll farms imbued their tweets with a large dose of negative emotions. However, the results showed that negative tweets were less liked and less retweeted as compared to the average tweet in the dataset. In terms of discrete emotions, the troll farms favored fear only to also receive negative dividends in virality.

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Photo by Daniela Holzer on Unsplash

Photo by Daniela Holzer on Unsplash

Why is it important?

Much of the media’s reporting on election interference stressed the foreign operatives’ strengths but rarely acknowledged that no one really knows for sure how to popularize social media messages. When Iranian and Russian operatives set up the fake Twitter accounts to influence the 2016 presidential election, the question of dissemination must have been front and center. As shown in the data, the troll farms favored negativity and fear as their strategy. Given that dataset encompasses all known fake accounts, the negative verdicts on the affective strategies are conclusive, at least for the dataset. That said, the Russian disinformation operation seemed more sophisticated than Iran's. The Russian troll farms spent from between early 2013 and late 2014 ingratiating themselves to the Twitter audience with upbeat/joyful tweets, only to revert to fear in time for the 2016 election. Iran’s campaign adhered to fear tactics throughout their accounts’ lifespan.

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