A major concern with internet news and social media in particular is the factionalization of the news audience along partisan, ethnic, and/or socio-demographic lines. We explore the role of recommender traits in the selection of content and psychological processing of news stories. We present the results of a web-experiment that shows how tie strength and homophily within actual Facebook social networks a ect article selection, then present the results of another large scale web-experiment on a national sample that documents the e ect of racial attributes of recommenders on our decisions to read content, and documents how readers' biases moderate how recommender traits a ect political preferences. Our ndings suggest that indeed homophily is a powerful force that drives the stories to which social media websites expose us (e.g., in our News Feeds), and which we choose to read. Paradoxically, our ndings also suggest that the racial and socioeconomic diversity of our social networks can impact our policy pref erences, by virtue of the fact that the story's recommender can a ect both the importance we place on a story and our political attitudes related to the story's content.
In September 2011, Pew released the latest in its annual "Views of the News Media" survey, showing that Democrats have moved closer to Republicans in their dissatisfaction with the performance of the news media. Across questions asked, of particular note were the trends above that showed that about 2/3 of partisans of all stripes believe that news stories are often inaccurate.
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