The two readings from this week, “Cyber Racism” and “Locate the Hate: Detecting Tweets against Blacks,” focus on the implications of a society that is so heavily engrossed in social media. The authors of both sources identify this as especially problematic when the material online gives both implicit and explicit messages about anti-minority sentiments.
Irene Kwok and Yuzhou Wang’s study, “Locate the Hate: Detecting Tweets against Blacks,” investigates the evolving nature of digital racism through the lens of the relatively new online social networking service, Twitter. Kwok and Wang’s article states that while African Americans make up only 14 percent of the American population, they more significantly make up 25 percent of the Twitter population. This means that a quarter of the users on Twitter are black. Keeping that in mind, it is stimulating to also take note of the research in their article that was shown prove that 51 percent of Americans express anti-black feelings. However, due to the billions of tweets made every day by twitter users, many of these anti-black tweets simply remain undetected.
Using Twitter as a digital platform, Kwok and Wang coded specific “hate” words from multiple and diverse Twitter accounts and placed them on a binary scale with two compartments titled “racist” or “nonracist.” Thus, each accounted Twitter user would then be placed into one of these two categories.
An example of a “racist” tweet on Kwok and Wang’s binary scale, as it contains the “hate word,” “nigger.”
The twitter user above, Shelly, would be coded as “racist” in Kwok and Wang’s study. This process had an accuracy rate of 76 percent. Yet even this classifying/coding process was not exactly accurate. Although 76 percent may seem high, and indeed it is, this system did not reach even close to all of the racist tweets on Twitter. In their article they further mention that some tweets did not contain the “hate words” they were looking for, but were still considered extremely racist. An example of this, which was also used in their article, is, “Why did Obama’s great granddaddy cross the road? Because my great granddaddy yanked his neck chain in that direction” (Kwok and Wang, 1622). As one can see here, this tweet does not contain any seemingly coded “hate words,” and as a result is a perfect example of how many tweets remained undetected in their study. However, the overall suggestion made in their article was that even though their research method was not as efficient as they would have hoped, it should provide a driving incentive for further research based on the results they did find.
The results found in Kwok and Wang’s study can be attributed to the conceptual theories in “Cyber Racism” by Jessie Daniels, as they both interplay with each other. Both readings lead its readers to conclude that racism online is an issue that is perhaps inevitable unless severe action on the matter is commenced. As an educated audience, citizens must recognize that there is currently a chain of racism that is perpetuated by negative online use. This chain begins with the surplus of online negativity (as Kwok and Wang note 51% of content is negatively associated with race). This massive amount of input leads people to internalize these messages. Specifically, this can be seen in children. As seen in the short video below, children at a very young age have already absorbed the negative messages/connotations associated with blackness into their psyche, and this effect can often cause these children to grow up with hatred of minorities. They then put their learned message out in the world through social media and the cycle continues, affecting more and more individuals.
In this video, the effects of Daniels, Kwok, and Wang’s message is seen. People are deeply affected by the messages of society. In the video almost every child associated the negative qualities (such as bad, ugly, or impolite) to the black dolls and the positive qualities (such as smart, nice, pretty) to the white dolls. This effect is directly correlated to messages of our society that they constantly hear around them.
This video further underscores the importance of “Cyber Racism” and “Locate the Hate: Detecting Tweets against Blacks.” The digital era is dominating our world more and more each day and it is imperative that we understand and are aware of its affects on people. Like Daniels states, the representation of white supremacy online is a demonstration of our actual world around us. This means that in a matter of seconds, with a click of a button, one is likely to see through the digital world how profound white supremacy is in the real world we live in.
When using Twitter, or any version of social media for that matter, everyone has a voice despite what his or her identity consists of. As the digital frontier becomes more and more integrated into our everyday living and breathing lives, it is essential that these negative attitudes be addressed. Online material no longer just stays online. It enters the collective conscious of the everyday real world. Although Daniels, Kwok, and Wang’s findings may appear small, one can see through analysis they have large and serious implications.
1) Although Daniels, Kwok, and Wang imply that cyber racism may be inevitable, what steps do we need to take as a society to overcome this problem?
2) Kwok and Wang’s study was very inefficient. However, despite how inefficient it was, it was still able to gather some serious data. Thus, further research should prove that their implications are right. How would they conduct a second study to gather most or all of the racist acts on social media?
3) Although cyber racism is formulated by a specific individual, should we hold Twitter, Facebook, and other major social media conglomerates accountable for enabling these people with more freedom of speech? Furthermore, what steps should be taken in an ideal world? Should the state or U.S. law take steps towards the rectification of cyber racism?
Daniels, Jessie. 2009. Cyber Racism: White Supremacy Online and the New Attack on Civil Rights. Lanham, Md.: Rowman & Littlefield Publishers. (selections)
“Doll Test.” Youtube. Youtube, 7 February 2012. Web. 14 Sept. 2014.
Kwok, Irene, and Yuzhou Wang. 2013. “Locate the Hate: Detecting Tweets against Blacks.” Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence, 1621–22.
“Racist Tweet Screenshot.” 2014. JPG file. https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&docid=JlayseIg0KanYM&tbnid=JJuDl7sgxHDZXM:&ved=0CAcQjRw&url=http%3A%2F%2Frepublicansareracists.com%2F2012%2F11%2F13%2Fgop-meltdown-2012-mapping-racist-tweets-from-the-2012-election%2F&ei=vSAqVNChOYaxyASwpoDgAw&bvm=bv.76477589,d.aWw&psig=AFQjCNEUZPwM87HCXc8pUYuVnEf7nobG2g&ust=1412133434700363
“The Impacts of Technology.” Youtube. Youtube, 15 April 2013. Web. 14 Sept. 2014.
“Twitter Screenshot.” 2014. JPG file. https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&docid=JCsQl6GklqoCsM&tbnid=UG8p4n8HrmOp6M:&ved=0CAcQjRw&url=http%3A%2F%2F3qdigital.com%2Fcategory%2Fsocialmedia%2Ftwitter%2F&ei=XCAqVNHcPJeAygSu6YCYBg&bvm=bv.76477589,d.aWw&psig=AFQjCNHfNlGO5TeDKbVYrb7g3QR2smiuPw&ust=1412133329979923