Factors That Determine Incidental News Exposure in the U.S.

The next speaker in this ICA 2018 session is Kjerstin Thorson, who begins by noting that incidental exposure is not simply random, but unevenly distributed across the online userbase. The idea of attraction may be useful here: what is it that attracts specific news content into a social media stream; who attracts incidental exposure? What practices produce attraction, or repel news content?

Who has these happy accidents of incidental exposure, then? In the weeks before the 2016 U.S. presidential election, better levels of education mean that users are more likely to be incidentally exposed. The factors that seem to matter here include an existing interest in news and politics; active curation and customisation of connections; friends who post about politics; targetting by news or political organisations; and algorithms. All of those factors are also unevenly distributed across the online population.

Such inequalities may be built into platform algorithms, of course, and this may shape the ‘algorithmic identities’ that platforms assume their users have. Higher-income and higher-education users may be assigned an algorithmic identity that is more interested in news, and therefore see more news content in their social media feeds, and to be targetted by ads from news organisations.