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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

#MeToo in Germany: The Hashtag Campaign in the Issue-Attention Cycle

Hoffmann, Julia Vanessa January 2018 (has links)
This thesis aims to interrogate how “issue-attention cycle” theory corresponds to online debates that address the issue of sexism, specifically the hashtag campaign #MeToo, in German online media. The issue-attention dynamics of #MeToo on Twitter are analyzed in order to understand the relationship between mainstream media and hashtag activism in Germany, and it is demonstrated what the #MeToo coverage can tell about issue-attention theory on the one hand, and how the theory can help to understand #MeToo on the other hand. To this end, the results of a content analysis of Twitter posts with #MeToo by four major German newspapers, representative of the German online media landscape, were compared to previous hashtag campaigns in Germany that addressed the same topic. In addition, five media experts as well as academics were interviewed, and their insights used to identify the issue-attention dynamics of #MeToo. Anthony Downs’ (1972) “issue-attention cycle” theory is then applied to the hashtag. The results show that so far there have been many ups and downs of attention in the lifecycle of #MeToo, but public attention has not ended. The research also finds that hashtags emanating from the United States, and especially from individuals related to the American entertainment industry, receive far more attention than corresponding hashtags originating in Germany, even though they address the same topic. Finally, and perhaps most significantly, the deployment of the issue-attention cycle showed that a modified model is necessary to address the fast-changing attention dynamics of hashtags on Twitter. Instead of a cycle, attention can be better demonstrated through waves. Adding the variables “new events” and the hashtag as a connector of events and issues to the model helps to better understand current media structures and their attention dynamics, which are strongly influenced by social media.

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