Disagreement may be a way to make online content spread faster, further: Study

The results come from an examination of posts labelled controversial on social news aggregation site Reddit. To perform the study, the researchers analysed more than 47,000 posts about cybersecurity in a Reddit dataset that was collected by the Computational Simulation of Online Social Behavior (SocialSim) program of the US Defense Advanced Research Projects Agency. The researchers found that these posts were seen by nearly twice the number of people and travelled nearly twice as fast when compared to posts not labelled controversial.

Reddit is one of the most visited websites in the US. A post is labelled controversial by a Reddit algorithm if it receives a certain number of polarized views, or a moderator can label a post with any number of comments as controversial. The posts analysed in the study included topics that wouldn't be considered traditionally controversial but were labelled as so by Reddit, such as a personal computer giveaway offer.

The research is important because it shows that disagreement may be a powerful way to get people to pay attention to messages, said study co-author Ivan Garibay, an associate professor in UCF's Department of Industrial Engineering and Management Systems. However, he advised caution to those inducing disagreement in their social media posts.

"There may be an incentive in terms of influence and audience size for a social media user to consistently include controversial and provocative topics on their posts," Garibay said. "This benefits the person posting the messages. However, controversial comments can be divisive, which could contribute to a polarized audience and society," Garibay added.

Reddit's definition of a controversial post, which tends to depend on increasing numbers of both likes and dislikes, is different from the traditional advertiser's definition of a controversial post, which would contain truly provocative or taboo messaging, said Yael Zemack-Rugar, an associate professor in UCF's Department of Marketing. "To give this idea life, you may like a recent ad for Toyota, and I may not," Zemack-Rugar said. "This will not make it controversial. But if the ad featured Colin Kaepernick, as the Nike ad did in 2018, after he recently refused to recite the national anthem during his games, now we are talking controversial. There is an underlying tone that is much deeper and more meaningful."

Reddit posts are also more akin to word-of-mouth communication since they are user-generated and not paid to advertise, she said. The study's findings are consistent with past research that has found that traditional controversy increases the spread of word of mouth and discussions online, especially when contributions are anonymous, as they somewhat are on Reddit, Zemack-Rugar said.

Of the more than 47,000 posts, approximately 23,000 posts were labelled controversial, and about 24,000 were noncontroversial. The researchers found an association between controversially labelled comments and the collective attention that the audience paid to them.

For the controversial posts, there were more than 60,000 total comments, whereas, for the noncontroversial posts, there were less than 25,000 total comments. A network analysis examining the reach and speed of the posts showed that nearly twice the number of people saw controversial content compared to noncontroversial content and that controversial content travelled nearly twice as fast.

The researchers limited posts in their analysis to those that had at least 100 comments. Jasser Jasser, a doctoral student in UCF's Department of Computer Science, and the study's lead author, said the findings highlight the need to better understand why the content labelled in Reddit as controversial spreads.

"The next step in this work is to analyze the language used to induce such controversy and why it brings the attention of the social media users," Jasser said. Study co-authors were Steve Scheinert, a senior solutions specialist with a professional services company and Alexander V. Mantzaris, an assistant professor in UCF's Department of Statistics and Data Science.