Online news selection and reading behavior
News type and reading goal
Bae’s research investigated how people select news in online environments, as these markets are typified by increased selectivity. Her driving questions asked how news content and the presence of photographs influenced selection. Using deviance theory, a dual systems model, and Annie Lang‘s Limited Capacity Model for Motivated Mediated Message Processing (LC4MP), Bae predicted that threatening stories would appeal most to consumers and the presence of photos would make stories more appealing.
Across two experiments, Bae found evidence bolstering the idea: if it bleeds it leads. Threatening stories had the greatest appeal but photos did little to make stories more appealing. Interestingly, while people were more drawn to threatening stories, they spent more time reading about innocuous subjects.
Ji’s work shows that it’s a depressing situation for those envisioning an end to the Digital Divide. His primary questions investigated how the diffusion of Internet Protocol Television (IPTV) affected cable companies (in terms of competition) and redlining practices of IPTV providers. In this application, redlining refers to the practice of IPTV providers denying service to homes within a certain area of a community (typically low-income households).
Using data from Indiana IPTV providers, Ji found statistically significant evidence of redlining among IPTV providers. Because of this, the benefits of competition (variety of programming, speed of internet connection, etc.) apply more to higher-income areas. Ji concluded that policy regulators should not only consider how better to promote competition, but also who the increased competition will benefit.