Suchergebnisse

Conventional models of agenda setting hold that mainstream media influence the public agenda by leading audience attention, and perceived importance, to certain issues. However, increased selectivity and audience fragmentation in today's digital media environment threaten the traditional agenda-setting power of the mass media. An important development to consider in light of this change is the growing use of social media for entertainment and information. This study investigates whether mainstream media can influence the public agenda when channeled through social media. By leveraging an original, longitudinal experiment, I test whether being exposed to political information through Facebook yields an agenda-setting effect by raising participants' perceived importance of certain policy issues. Findings show that participants exposed to political information on Facebook exhibit increased levels of issue salience consistent with the issues shared compared with participants who were not shown political information; these effects are strongest among those with low political interest.

Although we have a broad understanding of the factors that predict traditional forms of political participation, we know comparatively less about the determinants of online political participation. Among the limited research that explores the predictors of online political participation, news seeking is often found to be an important factor; however, many studies fail to consider selective exposure and the distinct influence of differing types of information. In this study, I ask, "What factors predict online participation, and what role does selective exposure play in this relationship?" Using a nationally representative sample ( N = 2,250) and a selection model to correct for biased estimates of online political participation, I find that online political participation is not well predicted by the same resource-related determinants that influence traditional participation; specifically, income and age are unrelated to online political participation among Internet users. Second, I find that exposure to political information that reinforces one's point of view predicts higher levels of online political participation when compared with differing information or information with no point of view. Finally, I conduct a subset analysis of partisan identifiers to examine differences in these relationships among Republicans and Democrats.

Studies demonstrate that citizenship norms and media use are important predictors of political behavior. However, it remains unclear how norms and patterns of media use influence different modes of political participation—both directly and in tandem. Here, we leverage original US survey data ( N = 2200) to clarify how people's attitudes about what it means to be a "good citizen" inform how they participate in politics, and whether certain types of media use moderate these relationships. In contrast to previous studies, we find that actualizing norms are associated with electoral, non-electoral, and individualized modes of political participation, but dutiful norms are not. In addition, although digital and traditional media use have distinct relationships with participation, there is little moderating influence. Collectively, these findings raise questions about whether the boundaries between dutiful and actualizing norms—and electoral and non-electoral participation, respectively—are still relevant in the contemporary media environment.

Open-ended survey questions can provide researchers with nuanced and rich data, but content analysis is subject to misinterpretation and can introduce bias into subsequent analysis. We present a simple method to improve the semantic validity of a codebook and test for bias: a "self-coding" method where respondents first provide open-ended responses and then self-code those responses into categories. We demonstrated this method by comparing respondents' self-coding to researcher-based coding using an established codebook. Our analysis showed significant disagreement between the codebook's assigned categorizations of responses and respondents' self-codes. Moreover, this technique uncovered instances where researcher-based coding disproportionately misrepresented the views of certain demographic groups. We propose using the self-coding method to iteratively improve codebooks, identify bad-faith respondents, and, perhaps, to replace researcher-based content analysis.

When a terrorist attack occurs, a natural response may be increased public concern about terrorism. But when a self-described Muslim perpetrates a terrorist attack, do negative attitudes toward Muslims also increase? If so, is this effect conditional on the nature of people's past personal experiences with Muslims? We present natural experiment data based on a 2015 web-based survey of 2105 non-Muslims in the US, a survey that happened to span the terrorist attacks in Paris on 13 November and San Bernardino on 2 December. We thus test Americans' feelings toward Muslims immediately before and after both an international and a domestic terrorist attack. We find that, although the attacks significantly affected Americans' concerns about radicalism both in the US and abroad, they did not negatively affect Americans' thermometer feelings toward Muslims in the aggregate—a null finding conditioned only slightly by the nature of past personal experiences with Muslims.