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Does the consumption of ideologically congruent news on social media exacerbate polarization? I estimate the effects of social media news exposure by conducting a large field experiment randomly offering participants subscriptions to conservative or liberal news outlets on Facebook. I collect data on the causal chain of media effects: subscriptions to outlets, exposure to news on Facebook, visits to online news sites, and sharing of posts, as well as changes in political opinions and attitudes. Four main findings emerge. First, random variation in exposure to news on social media substantially affects the slant of news sites that individuals visit. Second, exposure to counter-attitudinal news decreases negative attitudes toward the opposing political party. Third, in contrast to the effect on attitudes, I find no evidence that the political leanings of news outlets affect political opinions. Fourth, Facebook’s algorithm is less likely to supply individuals with posts from counter-attitudinal outlets, conditional on individuals subscribing to them. Together, the results suggest that social media algorithms may limit exposure to counter-attitudinal news and thus increase polarization.

Many have argued that digital technologies such as smartphones and social media are addictive. We develop an economic model of digital addiction and estimate it using a randomized experiment. Temporary incentives to reduce social media use have persistent effects, suggesting social media are habit forming. Allowing people to set limits on their future screen time substantially reduces use, suggesting self-control problems. Additional evidence suggests people are inattentive to habit formation and partially unaware of self-control problems. Looking at these facts through the lens of our model suggests that self-control problems cause 31 percent of social media use.

How do the media affect public support for democratic institutions in a fragile democracy? What role do they play in a dictatorial regime? We study these questions in the context of Germany of the 1920s and 1930s. During the democratic period, when the Weimar government introduced progovernment political news, the growth of Nazi popularity slowed down in areas with access to radio. This effect was reversed during the campaign for the last competitive election as a result of the pro-Nazi radio broadcast following Hitler’s appointment as chancellor. During the consolidation of dictatorship, radio propaganda helped the Nazis enroll new party members. After the Nazis established their rule, radio propaganda incited anti-Semitic acts and denunciations of Jews to authorities by ordinary citizens. The effect of anti-Semitic propaganda varied depending on the listeners’ predispositions toward the message. Nazi radio was most effective in places where anti-Semitism was historically high and had a negative effect in places with historically low anti-Semitism.

We empirically study the effects of broadband internet diffusion on local election outcomes and on local government policies using rich data from the U.K. Our analysis shows that the internet has displaced other media with greater news content (i.e. radio and newspapers), thereby decreasing voter turnout, most notably among less-educated and younger individuals. In turn, we find suggestive evidence that local government expenditures and taxes are lower in areas with greater broadband diffusion, particularly expenditures targeted at less-educated voters. Our findings are consistent with the idea that voters’ information plays a key role in determining electoral participation, government policies, and government size.

The authors propose a quantitative approach for describing entertainment products, in a way that allows for improving the predictive performance of consumer choice models for these products. Their approach is based on the media psychology literature, which suggests that people's consumption of entertainment products is influenced by the psychological themes featured in these products. They classify psychological themes on the basis of the \"character strengths\" taxonomy from the positive psychology literature (Peterson and Seligman 2004). They develop a natural language processing tool, guided latent Dirichlet allocation (LDA), that automatically extracts a set of features of entertainment products from their descriptions. Guided LDA is flexible enough to allow features to be informed by psychological themes while allowing other relevant dimensions to emerge. The authors apply this tool to movies and show that guided LDA features help better predict movie-watching behavior at the individual level. They find this result with both award-winning movies and blockbuster movies. They illustrate the potential of the proposed approach in pure content-based predictive models of consumer behavior, as well as in hybrid predictive models that combine content-based models with collaborative filtering. They also show that guided LDA can improve the performance of models that predict aggregate outcomes.

How users consume media has shifted dramatically as viewers migrate from traditional broadcast channels toward online channels. Rather than following the schedule dictated by television networks and consuming one episode of a series each week, many viewers now engage in binge watching, which involves consuming several episodes of the same series in a condensed period of time. In this research, the authors decompose users' viewing behavior into (1) whether the user continues the viewing session after each episode viewed, (2) whether the next episode viewed is from the same or a different series, and (3) the time elapsed between sessions. Applying this modeling framework to data provided by Hulu.com, a popular online provider of broadcast and cable television shows, the authors examine the drivers of binge watching behavior, distinguishing between user-level traits and states determined by previously viewed content. The authors simultaneously investigate users' response to advertisements. Many online video providers support their services with advertising revenue; thus, understanding how users respond to advertisements and how advertising affects subsequent viewing is of paramount importance to both advertisers and online video providers. The results of the study reveal that advertising responsiveness differs between bingers and nonbingers and that it changes over the course of online viewing sessions. The authors discuss the implications of their results for advertisers and online video platforms.

Privacy has been an enduring concern associated with commercial information technology (IT) applications, in particular regarding the issue of personalization. IT-enabled personalization, while potentially making the user computing experience more gratifying, often relies heavily on the user's personal information to deliver individualized services, which raises the user's privacy concerns. We term the tension between personalization and privacy, which follows from marketers exploiting consumers' data to offer personalized product information, the personalization-privacy paradox. To better understand this paradox, we build on the theoretical lenses of uses and gratification theory and information boundary theory to conceptualize the extent to which privacy impacts the process and content gratifications derived from personalization, and how an IT solution can be designed to alleviate privacy concerns. Set in the context of personalized advertising applications for smartphones, we propose and prototype an IT solution, referred to as a personalized, privacy-safe application, that retains users' information locally on their smartphones while still providing them with personalized product messages. We validated this solution through afield experiment by benchmarking it against two more conventional applications: a base non-personalized application that broadcasts non-personalized product information to users, and a personalized, non-privacy safe application that transmits user information to a central marketer's server. The results show that (compared to the non-personalized application), while personalized, privacy-safe or not increased application usage (reflecting process gratification), it was only when it was privacy-safe that users saved product messages (reflecting content gratification) more frequently. Follow-up surveys corroborated these nuancedfindings and further revealed the users' psychological states, which explained our field experiment results. We found that saving advertisements for content gratification led to a perceived intrusion of information boundary that made users reluctant to do so. Overall our proposed IT solution, which delivers a personalized service but avoids transmitting users' personal information to third parties, reduces users' perceptions that their information boundaries are being intruded upon, thus mitigating the personalization-privacy paradox and increasing both process and content gratification.

We develop a model of advertising markets in an environment where consumers may switch (or “multi-home”) across publishers. Consumer switching generates inefficiency in the process of matching advertisers to consumers, because advertisers may not reach some consumers and may impress others too many times. We find that when advertisers are heterogeneous in their valuations for reaching consumers, the switching-induced inefficiency leads lower-value advertisers to advertise on a limited set of publishers, reducing the effective demand for advertising and thus depressing prices. As the share of switching consumers expands (e.g., when consumers adopt the Internet for news or increase their use of aggregators), ad prices fall. We demonstrate that increased switching creates an incentive for publishers to invest in quality as well as extend the number of unique users, because larger publishers are favored by advertisers seeking broader “reach” (more unique users) while avoiding inefficient duplication.

This paper investigates the drivers and inhibitors of Internet privacy concern. Applying the Multidimensional Development Theory to the online environment, we identify the important factors under four dimensions—i.e., environmental, individual, information management, and interaction management. We tested our model using data from an online survey of 2417 individuals in Hong Kong. The results show that the factors under all four dimensions are significant in the formation of Internet privacy concern. Specifically, familiarity with government legislation, Internet knowledge, benefit of information disclosure, privacy protection, and social presence reduce Internet privacy concern, while individuals' previous privacy invasion experience, risk avoidance personality, and sensitivity of information requested by websites increase Internet privacy concern. We conducted an analysis of unobserved heterogeneity to confirm the significance of these factors. A follow-up moderation analysis shows that the individual factors (i.e., previous privacy invasion experience, risk avoidance personality, and Internet knowledge) moderate the effects of the information management factor (i.e., information sensitivity) and the interaction management factors (i.e., privacy protection and social presence). The findings provide an integrated understanding of the formation of Internet privacy concern.

The media industry has undergone a fundamental shift over the past decade as new online distribution channels have proliferated in an unprecedented manner. Although mobile devices have experienced rapid adoption among consumers, their effect on consumer behavior and their subsequent implications for publishers and advertisers have yet to be understood. The authors examine consumers’ news consumption behavior on mobile news websites in response to the introduction of a mobile news app. Pseudo-panel analysis based on repeated cross-sectional data suggests that the introduction of a mobile app by a major national media company leads to a significant increase in demand at the corresponding mobile news website. In addition, the authors report that this effect is greater for consumers with (1) greater appreciation for concentrated news content, (2) stronger propensity for a particular political viewpoint, and (3) fewer time constraints. The results are consistent with the interpretation that the adoption of a provider’s news app stimulates corresponding mobile news website visits. The authors discuss the implications of these findings for advertisers, media publishers, and policy makers.