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To knee or not to knee: An examination of Twitter visual content during the 2017 NFL national anthem protests in the United States
Lin, Trisha Tsui-Chuan
Visual content analysis
|Issue Date: ||2018-09-03 15:55:34 (UTC+8)|
|Abstract: ||Past research has delved into collective actions and political activism. However, few studies analyze the communication patterns of visual content generated on social media throughout protest events in relation to polarized political issues. Given the impacts of Twitter mobilizers to shape online opinions of protesters, this content analysis study examined Twitter image tweets during the 2017 National Football League (NFL) national anthem protests (NAP) in the United States. In order to understand visual communication trends on Twitter during the protest, this study will utilize the social identity theory (Tajfel and Turner, 1979) and Van Zomeren et al.’s (2012) dual pathway model (DDPM). The theoretical framework of integrating SIT and DDPM will facilitate the understanding of how social identity, grievances, and coping approaches (emotional route: affective responses; instrumental route: efficacy) factor into social media image content during a polarized protest.|
This study analyzed tweeted images shared when the national anthem protests peaked in web search penetration. It collected image tweets with the Twitter Advanced Search function and used top tweet filter under the #TakeAKnee hashtag. This research in total analyzed 1,400 viral NAP tweet images from September 24, to October 21, 2017. Based on research questions and past studies, xx codes have developed with xx emerging codes from the data.
The visual content analysis showed that NAP supporters’ posts were primarily related to the social identity of minority support; however, the visual content for constructive patriotism and sports fandom was minimal. Images depicting police brutality were scarce, possibly due to the peaceful nature of the NAPs. In terms of grievances, images regarding anti-protest mobilizers such as Donald Trump were more prominent in the dataset. Consistent with past research, reciprocal affective responses (i.e. sympathy and admiration) were expressed more in the image tweets than shared affective responses (i.e. anger and sarcasm). Lastly, in regards to temporal changes for key codes, the themes of majority of image tweets were not influenced by offline events or news outlets’ agenda setting over time. This indicates that the online communication patterns of NAP supporters do not always repeat or continue the topics in various news outlets and offline events. As the dataset did not follow an identifiable pattern across the codes and subcodes in regards to temporal changes, common trends instead included image tweet spikes and volume alignment between codes on days that corresponded with offline events.
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|Source URI: ||http://thesis.lib.nccu.edu.tw/record/#G1054610301|
|Data Type: ||thesis|
|Appears in Collections:||[國際傳播英語碩士學程] 學位論文|
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