Do users tend to consume only like-minded political information online? We point to two problems with the existing knowledge about this debate. First, the measurement of media preferences by the typical means of surveys is less reliable than behavioral data. Second, most studies have analyzed only the extent of online exposure to like-minded content, not the users’ complete web-browsing repertoire. This study used both survey data and real-life browsing behavior (661,483 URLs from 15,976 websites visited by 402 participants) for the period 7 weeks prior to the 2013 Israeli national elections. The results indicate that (1) self-report measurements of ideological exposure are inflated, (2) exposure to online ideological content accounted for only 3% of total online browsing, (3) the participants’ media repertoires are very diverse with no evidence of echo chambers, and (4) in accordance with the selective exposure hypothesis, individuals on both sides are more exposed to like-minded content. The results are discussed in light of the selective exposure literature.

Many blame partisan news media for polarization in America. This paper examines the effects of liberal, conservative, and centrist news on affective and attitude polarization. To this end, we rely on two studies that combine two-wave panel surveys (N1 = 303, N2 = 904) with twelve months worth of web browsing data submitted by the same participants comprising roughly thirty-eight million visits. We identify news exposure using an extensive list of news domains and develop a machine learning classifier to identify exposure to political news within these domains. The results offer a robust pattern of null findings. Exposure to partisan and centrist news websites—no matter if it is congenial or crosscutting—does not enhance polarization. These null effects also emerge among strong and weak partisans as well as Democrats and Republicans alike. We argue that these null results accurately portray the reality of limited effects of news in the “real world.” Politics and partisan news account for a small fraction of citizens’ online activities, less than 2 percent in our trace data, and are nearly unnoticeable in the overall information and communication ecology of most individuals.

The online environment dramatically expands the number of ways people can encounter news but there remain questions of whether these abundant opportunities facilitate news exposure diversity. This project examines key questions regarding how internet users arrive at news and what kinds of news they encounter. We account for a multiplicity of avenues to news online, some of which have never been analyzed: (1) direct access to news websites, (2) social networks, (3) news aggregators, (4) search engines, (5) webmail, and (6) hyperlinks in news. We examine the extent to which each avenue promotes news exposure and also exposes users to news sources that are left leaning, right leaning, and centrist. When combined with information on individual political leanings, we show the extent of dissimilar, centrist, or congenial exposure resulting from each avenue. We rely on web browsing history records from 636 social media users in the US paired with survey self-reports, a unique data set that allows us to examine both aggregate and individual-level exposure. Visits to news websites account for about 2 percent of the total number of visits to URLs and are unevenly distributed among users. The most widespread ways of accessing news are search engines and social media platforms (and hyperlinks within news sites once people arrive at news). The two former avenues also increase dissimilar news exposure, compared to accessing news directly, yet direct news access drives the highest proportion of centrist exposure.

Wikipedia, a publicly edited online encyclopedia, is accessed by millions of users for answers to questions from trivial to high-stakes topics like health information. This new type of information resource may pose novel challenges for readers when it comes to evaluating the quality of content, yet very little is known about how Wikipedia readers understand and interpret the material they find on the site. Do people know that anyone can edit the site? And if so, what does this fact lead them to believe about the reliability of Wikipedia or particular articles therein? This study analyzes the information-seeking behavior of a diverse group of 210 college students from two Midwestern US universities as a first step towards addressing these questions. This paper found that a few students demonstrated in-depth knowledge of the Wikipedia editing process, while most had some understanding of how the site functions and a few lacked even such basic knowledge as the fact that anyone can edit the site.

Outside of a lab environment, it has been difficult for researchers to collect both behavioral and self-reported Web use data from the same participants. To address this challenge we created Roxy, software that collects real-world Web-use data with participants' informed consent. Roxy gathers Web log data as well as the text and HTML code of each page visited by participants. In this workbench note we describe Roxy's data gathering capabilities and search functions, then illustrate how we used the software in a multimethod study. The use case examines selective exposure to political communication during the November 2010 U.S. general election campaign.