200,313 research outputs found

    The CSI Effect : Exposing the Media Myth

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    Barriers to obesity communication - Power, habitus and hidden assumptions

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    Communication on health issues often founders on the avoidance or denial of key messages by intended recipients. This paper explores the development and application of a research methodology combining elements of Pierre Bourdieu’s work on the unconscious nature of practice with Gerhard Maletzke’s psychological model of communication. This combination was designed to elicit deeper responses than those often found in health communication research. This alternative methodological approach was used to evaluate a year-long, city-wide anti-obesity campaign in Sheffield, UK, which targeted key gatekeepers in the message chain; their responses generate useful insights into resistance to uncomfortable communication. The paper concludes with suggestions for addressing communication about obesity and potentially other uncomfortable health and social topics

    Intersections and differentiations: a corpus-assisted discourse study of gender representations in the British press before, during and after the London Olympics 2012

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    This study examines the impact of a global sports event on gender representations in media reporting. Whereas previous research on gender, sport and media has been mainly concerned with sports events in the North American or Australian context, this study investigates the British media reporting before, during and after the London Olympics 2012. Our study follows the approach of Corpus-Assisted Discourse Studies (CADS) and uses both quantitative and qualitative research procedures. The results reveal more balanced gender representations during the London Olympics in that the ‘regular’ biased associations were supressed in favour of positive references to female achievements. However, little carry-though of the ‘gains’ was noted. Also, this study shows that the positive associations intersected with national sentiments and were used to celebrate the nation-state. At the same time, some subtle resistance was observed to accepting as ‘truly’ British the non-white athletes and those not born in Britain

    Modeling the formation of attentive publics in social media: the case of Donald Trump

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    Previous research has shown the importance of Donald Trump’s Twitter activity, and that of his Twitter following, in spreading his message during the primary and general election campaigns of 2015–2016. However, we know little about how the publics who followed Trump and amplified his messages took shape. We take this case as an opportunity to theorize and test questions about the assembly of what we call “attentive publics” in social media. We situate our study in the context of current discussions of audience formation, attention flow, and hybridity in the United States’ political media system. From this we derive propositions concerning how attentive publics aggregate around a particular object, in this case Trump himself, which we test using time series modeling. We also present an exploration of the possible role of automated accounts in these processes. Our results reiterate the media hybridity described by others, while emphasizing the importance of news media coverage in building social media attentive publics.Accepted manuscrip

    Search Bias Quantification: Investigating Political Bias in Social Media and Web Search

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    Users frequently use search systems on the Web as well as online social media to learn about ongoing events and public opinion on personalities. Prior studies have shown that the top-ranked results returned by these search engines can shape user opinion about the topic (e.g., event or person) being searched. In case of polarizing topics like politics, where multiple competing perspectives exist, the political bias in the top search results can play a significant role in shaping public opinion towards (or away from) certain perspectives. Given the considerable impact that search bias can have on the user, we propose a generalizable search bias quantification framework that not only measures the political bias in ranked list output by the search system but also decouples the bias introduced by the different sources—input data and ranking system. We apply our framework to study the political bias in searches related to 2016 US Presidential primaries in Twitter social media search and find that both input data and ranking system matter in determining the final search output bias seen by the users. And finally, we use the framework to compare the relative bias for two popular search systems—Twitter social media search and Google web search—for queries related to politicians and political events. We end by discussing some potential solutions to signal the bias in the search results to make the users more aware of them.publishe
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