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In the past few years, the American public has faced many domestic and divisive hardships including, but not limited to, those centered on racial prejudice and police brutality (LeFebvre & Armstrong, 2016). In fact, these two issues are what sparked the NFL national anthem protests (NAPs), in which athletes kneel during the national anthem. After President Trump's tweets to openly condemn the NAPs in 2017, public opinions showed polarized responses. In order to analyze the communication patterns and meanings of NAPs visual Tweets, this study is grounded upon the social identity theory (SIT; Tajfel & Turner, 1979) and adapts Van Zomeren et al.'s (2012) dynamic dual pathway model (DDPM). This study's proposed research framework allows for greater understanding of how social identity, grievances, and coping approaches (emotional route: affective responses; instrumental route: efficacy) factor into image content shared during a polarized protest. In order to understand social media discussions of NAPs' supporters the NFL, this study conducts visual content analysis of relevant Twitter image tweets after Trump's posts aroused heated debates. This investigation attempts to understand how protest supporters used different digital coping methods in response to protest opposition (such as different affective responses or responses that are efficacy-eliciting). This study uses images as the primary data source for Twitter content analysis because they have a different intention than text-based social media messages as images present symbols to users, allowing them to establish references quicker. This study collects image tweets using the most viral hashtag #TakeAKnee via the Twitter Advanced Search function from September 24, 2017 (the peak of web search penetration for NAPs) to October 21, 2017 (when the NAPs web search penetration dropped after the second peak). The code scheme includes 4 codes and 18 sub-codes that has been developed based on relevant theoretic concepts about protests. Emerging new codes can be recognized from recurrent patterns that appear during the data analysis. Along with the researcher, another trained coder analyzed the image tweets, resulting in acceptable intercoder reliability. The findings of this study have shed light on the complex nature of the NFL national anthem protests and the social identity projection for Twitter users who support the NAPs. Specifically, the social identity of minority support was most prevalent while the social identities of constructive patriotism and sports fandoms was minimal, suggesting that although anti-protest mobilizers may be able to increase the volume of online dialogue, they are unable to shift the focus of the protest away from its original purpose. Additionally, reciprocal affective responses (i.e. sympathy and admiration) were expressed more in the image tweets than shared affective responses (i.e. anger and sarcasm), contradicting previous studies on protest emotions and collective action motivators. Practically, this research is significant because as the NAPs could possibly start anew in the 2018 NFL season, addressing the concerns of the citizens (identified through visual analysis of Twitter images) can be beneficial in resolving the primary issues surrounding the protests. Finally, as few studies have used visual tweet analysis to investigate social movements or protests (see Cowart et. al, 2016; Kharroub & Bas, 2016; Wetzstein, 2017), this study contributes to this emerging form of content analysis.
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