Two key features robustly describe ideological differences in society: (i) individuals persistently disagree about objective facts; (ii) individuals also disagree about which sources can be trusted to provide reliable information about these facts. We develop a model in which these patterns arise endogenously as the result of small deviations from Bayesian information processing. Individuals re...

This article examined, thought a Cultural Historical Activity Theory lens, how immersiveor pervasive environments and pedagogical agents could more easily support social collaboration as foundation of contemporary learning theory. It is argued that the fundamentalism-liberationism contradiction (learn from versus learn with technology) is no longer justifiable as contemporary technology tools (...

In table 2 we present standard errors for our main estimates. For estimates that come from MRI, the GSS or the CNES, we compute standard errors through a nonparametric bootstrap over samples of respondents. For estimates that come from comScore aggregate data, that is not an option. Instead we perform a parametric bootstrap in which we model the share conservative of each website as an independ...

The analysis in the paper suggests that (i) if news sites were less vertically differentiated, segregation would increase considerably, and (ii) if users did not visit multiple sites, more users would have extremely high or low conservative exposure. To make these hypotheses more precise, we specify and estimate a simple model of Internet news demand, and use it to simulate segregation and cons...

It is widely thought that news organizations exhibit ideological bias, but rigorously quantifying such slant has proven methodologically challenging. Through a combination of machine learning and crowdsourcing techniques, we investigate the selection and framing of political issues in 15 major U.S. news outlets. Starting with 803,146 news stories published over 12 months, we first used supervis...