Researchers from a collection of institutions have published data that suggests Internet users demonstrate a pattern of behavior similar to that found in other media; specifically, how they look for and propagate information they find.
It’s not exactly breaking news that people tend to limit their exposure to news sources that offer information in line with their personal beliefs. But when it’s a collection of people doing the same thing – that is, reading and citing the same sources – it creates what’s referred to as “echo chambers.”
The aforementioned group of researchers used this understanding to analyze the behavior patterns of users on various social media sites — what they found was a very similar type of information processing behavior, especially with users on Facebook.
Now, it should be noted that at the start of the study, it was suspected that Facebook users accessed and consumed news information similar to how news outlet information is normally processed. To confirm this, the group accessed publicly available data via Facebook’s graph application program interface and used it as the foundation for all of their information.
For those curious, this information provided the researchers with data regarding user content preferences. The team divided the content “type” into different categories (conspiracy theories, engineering news, sports highlights, etc.). They also made a datasheet consisting of data from what was referred to as “troll pages” — basically, the “type” of comments that people leave on other people’s pages. All data was obtained from 2010 to 2014, and was run across analysis software on the datasheet to search for and display pattern information.
Upon analyzing the data, the researchers found evidence that Facebook users, in particular, tend to engage in creating echo chambers, whereby they more or less encase themselves in digital environments consisting of news feeds that profess the same beliefs as their own. The team suggests this behavior can serve as an explanation to such peculiar occurrences as the widespread rejection of global warming, among others.
The researchers go on to suggest that there is now a new trend among users who are actively looking to make their way into echo chambers with what they believe to be truthful information, for the purpose of reaching a larger audience; this, as opposed to sharing the same message time and again to smaller subgroups. The most successful measure in this regard has been the buying of advertisements to run alongside these group pages and discussions.
For more information about this study between programming and social sciences, check out the abstract below:
The wide availability of user-provided content in online social media facilitates the aggregation of people around common interests, worldviews, and narratives. However, the World Wide Web (WWW) also allows for the rapid dissemination of unsubstantiated rumors and conspiracy theories that often elicit rapid, large, but naive social responses such as the recent case of Jade Helm 15––where a simple military exercise turned out to be perceived as the beginning of a new civil war in the United States. In this work, we address the determinants governing misinformation spreading through a thorough quantitative analysis. In particular, we focus on how Facebook users consume information related to two distinct narratives: scientific and conspiracy news. We find that, although consumers of scientific and conspiracy stories present similar consumption patterns with respect to content, cascade dynamics differ. Selective exposure to content is the primary driver of content diffusion and generates the formation of homogeneous clusters, i.e., “echo chambers.” Indeed, homogeneity appears to be the primary driver for the diffusion of contents and each echo chamber has its own cascade dynamics. Finally, we introduce a data-driven percolation model mimicking rumor spreading and we show that homogeneity and polarization are the main determinants for predicting cascades' size.
Download the paper, entitled The spreading of misinformation online, which was published in Proceedings of the National Academy of Sciences .
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