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Racism

Though we increasingly understand what happens online is not any less ‘real’ than what happens offline, it can be easy for some to perceive that they are talking to a computer when they post on social media, rather than publishing within a space of public social communication. For example, there have been many cases on Twitter and Facebook where disgruntled employees post inappropriate messages about their bosses, which they would not have uttered offline. The logic here is that the act of typing on a keyboard can sometimes lead to a perception that what you type is somehow less ‘real’ or perhaps kind of trivial.

 

But, of course, it is no less real or trivial. Social media sites such as Twitter have been host to racialized talk about immigration or can respond to events in racialized ways (for example Charlene White’s refusal to wear a poppy). In terms of anti-racism, Twitter users often police the medium for ‘casual’ forms of racism. It is the latter that I have taken a particular interest in within my research of social media and Twitter specifically. So when Madonna used the N-word on January 17, 2014 via Instagram, my casual racist sensor went off. For those not familiar with this incident, Madonna Instagrammed a picture of her son Rocco Ritchie while boxing, adding the caption: “No one messes with Dirty Soap! Mama said knock you out! #disni**a”. Madonna’s million plus Instagram followers received the image, which nearly instantaneously circulated to Twitter and  its diverse audiences. Not only is the use of the N-word clearly inappropriate, but embedding it within a racial hashtag contributes to larger hashtag-based casual racist discourses on Twitter and other social media. Madonna’s Instagram photo caption reveals that she sees a certain normalcy of the N-word. More dangerously, her worldwide celebrity status, legitimizes racial hashtags through her casual use of the N-word on Instagram.

 

Though it is important to make larger arguments about how the Madonna incident is a case of casual racism which has major implications, I think it is also important to understand the micro-level interactions on social media which Madonna prompted. To do this, I first collected all tweets with the #disni**a hashtag and then did the same for all tweets containing ‘Madonna’. The latter had very little to add in terms of data that was not already encompassed by the former. As #disni**a was a more inclusive search term, I created a graph of this network.

#disni__a network graph

[squares represent users with more than 1,000 followers and the size of the user icons is scaled by the number of RTs or @mentions].

 

The noticeable black square (between the blue and purple squares) represents Madonna (rather than her tweeting out, people are tweeting at her). The blue square represents an East Asian-American actor/comedian on MTV (@Traphik ; 420,000 followers) who tweeted “Lol Madonna hashtagged a pic with #disnigga!? Do u kids see what uve done! It’s like grandpa saying “yo homie G” cuz it’s all he hears!”. The purple square represents a black female blogger (@luvvie) with over 27,000 followers who had two tweets heavily retweeted, “Madonna talmbout she called her son #DisNigga as term of endearment. I wanna lock her in a stadium of seats so she can pick plenty to have” and “If Madonna is calling her white son #DisNigga, what is she calling her little Malawian son? I’m unable to deal.” It is interesting that the two centers of the tweet network for #disni**a are not white and both use humor to interrogate Madonna’s Instagram incident. From a social graph perspective, they steered the conversation on Twitter.

 

Madonna’s racist outburst was clearly racist and was covered in the popular press as such. The ‘thought leaders’ on Twitter around the #disni**a hashtag, however, saw this as an opportunity to both ridicule Madonna (e.g. PTraphik labeling Madonna as an out of touch Grandma), but also reflect on her use of the racial slur. Madonna made clear that she did not intend the comment as ‘a racial slur’ and that she is ‘not a racist’. However, this incident highlights the extreme prevalence of racialized language on social media, when even a self-purported liberal celebrity who pushed gender boundaries in the 80s/90s uses a racialized hashtag. I think this incident makes clear that we should not be lulled into a false sense of security of de-racialized virtual spaces, but that the virtual can also give us glimpses into peoples’ backstage lives, which we would not usually have access to offline. Ultimately, the Material Girl has been shamed on Twitter. It would have been nice to see more of a critical engaged discourse on Twitter about the incident, but that is not how social media usually operates.

A version of this blog has been published by The Runnymede Trust on their Race Card blog.

In my research of large Twitter data sets, I have been regularly studying trending topics. Most of the time, trending topics encourage monologic behavior on Twitter. For example, see the relatively monologic network graph below of #ThreeWordsSheWantsToHear (a hashtag which warrants serious  critical, dialogic engagement of gender issues).

#ThreeWordsSheWantsToHear Network Graph

I have been investigating the #accidentalracist hashtag from this past Monday (April 8, 2013). The hashtag formed in response to the new Brad Paisley and LL Cool J song titled ‘Accidental Racist’ (video below).

The Huffington Post labeled the song ‘a controversial one, to say the least’ and features the singer donning a Confederate flag. Forbes observed that the song set ‘off a firestorm on social media’.

Given the controversial nature of this hashtag, I was curious whether the tag was encouraging monologic or more dialogic behavior. It turns out that the 1504 tweets I sampled (from 9:56 p.m. to 11:18 p.m. UTC on April 8, 2013) actually exhibited far more interaction than one would expect in a trending topic-based network. Take a look at the social network analysis map below and let me know your thoughts!

#accidentalracist social network map

#accidentalracist social network map

 

And, as @sociographie, mentioned in a Twitter chat we had, it is important not to solely prioritize relationships in a network graph of trending topics. That is why I have retained isolates. Below, you can also find some aggregate information on the tweets.

Top URLs in Tweet in Entire Graph Entire Graph Count
http://thehairpin.com/2013/04/accidental-racist 28
http://bit.ly/10B2ZPs 21
http://www.theatlantic.com/entertainment/archive/2013/04/brad-paisley-and-ll-cool-j-show-how-not-to-sing-about-the-confederate-flag/274799/ 17
http://ow.ly/jS1zt 10
http://www.youtube.com/watch?v=uC6Ev5o5r7Y 5
http://mashable.com/2013/04/08/brad-paisley-accidental-racist/ 4
http://jezebel.com/brad-paisleys-accidental-racist-song-is-terrible-ho-471297837 3
http://rapgenius.com/Brad-paisley-accidental-racist-lyrics 3
http://www.youtube.com/watch?v=xvgCvT9xX7A 2
http://www.youtube.com/watch?v=a_qbt1EVuw8 2
Top Domains in Tweet in Entire Graph Entire Graph Count
thehairpin.com 28
bit.ly 27
youtube.com 23
theatlantic.com 17
ow.ly 13
youtu.be 10
j.mp 4
mashable.com 4
tinyurl.com 4
jezebel.com 3
Top Hashtags in Tweet in Entire Graph Entire Graph Count
accidentalracist 1493
llcoolj 26
bradpaisley 23
intentionalbeatdown 17
thewalkingdead 7
negrobush 5
occupy 5
ows 5
oppression 5
llcooljoke 4

 

 

“I stand, a trespasser in his camp, hearing echoes—Chink, gook, Jap, Charlie, GO HOME, SLANT-EYES!—words that, I believe, must ‘have razored my sister Chi […] What vicious clicking sounds did they make in her Vietnamese ears, wholly new to English?” (Pham 1999: 6-7)

 I recently travelled to Utrecht, Holland and couldn’t help but recall the lines above from Pham’s Catfish and Mandala. I had just taken a train from Amsterdam and was standing in Utrecht Station gobsmacked.

A restaurant called ‘Charlie Chiu’s’ was busily filling up with Dutch customers. Pham’s words rushed into my head. ‘Charlie Chiu’s’ had as its logo: ‘Charlie’ with ‘SLANT-EYES’. Its heavily racialized logo was clearly drawing from pejorative essentialisms which encompass ‘gook’ and ‘Jap’ (and many other Asian slurs).

The reason I was in Utrecht was to attend the Digital Crossroads Conference, a conference exploring race and migration online. After a short walk from the station, I was soon listening to Lisa Nakamura’s keynote address, which discussed forms of online racism (including ‘trash talk’ on YouTube). As she spoke about race and racism on YouTube, the image of Charlie Chiu’s remained and reminded me of the continued pervasiveness of racism in Holland. Particularly, Geert Wilders, the right-wing Dutch politician, has encouraged open Islamophobia in the Netherlands (Wieringa 2011). Though my work has investigated ubiquitous online racism, I often forget to write about persistent racism offline. ‘Charlie Chiu’s’ is emblematic of larger currents of race in the Netherlands (Essed and Trienekens 2008). I would be very interested in hearing from readers about their thoughts.

References:

Essed, P. and Trienekens, S. 2008 ”Who wants to feel white?’ Race, Dutch culture and contested identities’, Ethnic and Racial Studies 31(1): 52-72.

Pham, A. X. 1999 Catfish and mandala : a two-wheeled voyage through the landscape and memory of Vietnam, 1st Edition, New York: Farrar, Straus and Giroux.

Wieringa, S. E. 2011 ‘Portrait of a Women’s Marriage: Navigating between Lesbophobia and Islamophobia’, Signs 36(4): 785-793.