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Monthly Archives: April 2013

Please cite this as: Murthy, D. (2013), “’Hate-watching’ and Twitter”, iSociology,  http://www.dhirajmurthy.com/hate-watching-and-twitter

In my Twitter research, I have been exploring ‘social television watching’. There are two key points which come to mind regarding how the rise of social media has impacted our approach to television-viewing generally. First, scholarship on television has seen TV viewing as ‘parasocial’, an unbalanced relationship where television viewers feel ‘intimacy at a distance’ with celebrity actors (MR Levy 1979). In other words, TV viewers perceive an intimate relationship, where they have the illusion that they ‘know’ the celebrity on screen; however, the celebrity knows nothing of the television watcher. The promise, or at least perception, of social media such as Twitter is that this parasociality may be broken down or challenged one @-mention at a time by the likes of Ashton Kutcher. So the impact here is a perceived decrease of parasociality (a decrease in the traditional gap between television viewer and celebrity on the screen).

Additionally, social media, by encouraging television audience members to be quite active, tweeting under #thefollowing or #dexter can form engaged public audiences, which include both fans who know each other and fans who do not. This social TV watching is powered by social media use via mobile smartphones and laptops. Interestingly, an argument can be made that this increases our sociability while engaging in an activity which many have viewed as becoming less and less social (in juxtaposition to historical TV watching as a family or other group).

Hate-watching has been a part of television since its inception. It’s not that Twitter and other social media encourage hate watching per se, but that social media make it easier to publicly hate-watch. In other words, shows like Single Ladies or Toddlers & Tiaras would have had hate-watchers with or without social media. It is not only the publicness of hate watching that has changed, but also that it is real time, global, and not limited to one’s living room or to a single telephone call. What social media does is enable a ‘networked public’ (see ‘Networked’ by Barry Wellman) to hate-watch together. Additionally, after Emily Nussbaum’s 2012 New Yorker piece, ‘Hate-Watching “Smash”‘, Twitter has seen many incidents of people tweeting under #hatewatching and similar hash tags shows that are the top of their hate-watch list. Twitter can ultimately egg people on to hate watch (especially during the network broadcast of a show or in the immediate days after the show is aired).

As mentioned above, social media creates new social communities and formations. Often, these are focused around particular events (something I discuss in my book). In the case of television, these events are particular TV shows. Events encourage social responses. My view is that hate-watching is not more popular today per se. Rather, it is the way in which we hate-watch that has changed. Melrose Place in the 90s comes to mind here! Though by no means the same as hate-watching, the best term to describe similar historical processes of this type of television watching is ‘guilty pleasure’. An Associated Press article in 2002 refers to Jerry Springer shows in this vein.

What is different, and why we may perceive hate-watching to be more popular today, is that Twitter makes it very easy to publicly broadcast your hate-watching. Not only that, but the social engagement of rapid @-mentions between hate-watchers leads us to think it is on the rise. Not only is it very public and in your face now, but it is highly networked, real-time, and global.

[This post should be cited when referenced and not reproduced without prior permission]

On April 12, 2013 I ran the Collaborative Organizations and Social Media Conference (#2013COSM). The conference considered the ways in which the developing scholarship on social media and social networking might be incorporated into thinking critically about how social computing may be affecting and even forming organizations.

Among the questions and areas raised were:

·       How do we evaluate the utility of social computing technologies to virtual organizations?

·       How do social media and social networking technologies shape organizational structures?

·       Can social media and social networking enhance trust relationships within organizations?

·       How do we identify and understand social media cyberinfrastructures within virtual teams?

·       What can social network analysis tell us about how social media affects collaborative organizations and processes?

In the spirit of collaborative social media, the event was LiveStreamed and had a strong engagement on Twitter both by attendees as well as LiveStreaming participants. Below is a graph of Twitter activity, which included 45 Twitter participants and 191 unique tweet actions (i.e. edges). The average geodesic distance was 1.94, making this a pretty highly intermeshed group!

#2013COSM Tweet Interactions for Collaborative Organizations and Social Media Conference

#2013COSM Tweet Interactions for Collaborative Organizations and Social Media Conference

And when you remove ‘followed’ edges:

#2013COSM Tweets without Follows relationships

#2013COSM Tweets without Follows relationships

 

Other statistics about the #2013COSM corpus can be found below:

Top Links in Tweet in Entire Graph Entire Graph Count
http://new.livestream.com/accounts/3511964/events/2003155 60
http://digitalcommons.bowdoin.edu/cosm/2013/program/ 8
http://thenewinquiry.com/essays/the-myth-of-cyberspace/ 4
http://www.dhirajmurthy.com/collaborative-organizations-and-social-media-conference/ 3
http://joc.sagepub.com/content/10/1/13.full.pdf+html 3
http://thesocietypages.org/cyborgology/2013/03/21/materiality-matters/ 2
http://digitalcommons.bowdoin.edu/cosm/2013/program/16/ 2
http://digitalcommons.bowdoin.edu/cosm/2013/ 1
http://www.sciencedirect.com/science/article/pii/S0304422X1100012X 1
http://schradie.com/research/ 1
Top Domains in Tweet in Entire Graph Entire Graph Count
livestream.com 60
bowdoin.edu 12
thenewinquiry.com 4
dhirajmurthy.com 3
sagepub.com 3
thesocietypages.org 2
sciencedirect.com 1
schradie.com 1
tinyurl.com 1
academia.edu 1
Top Hashtags in Tweet in Entire Graph Entire Graph Count
2013cosm 252
sociology 7
socialmedia 3
measurement 2
creativity 2
livestream 2
jenniferearl 1
prosumer 1
soc245 1
unternehmen 1
Top Words in Tweet in Entire Graph Entire Graph Count
2013cosm 252
rt 94
social 59
dhirajmurthy 46
media 42
earl 39
livestream 38
pjrey 35
nathanjurgenson 34
nicole_ellison 31
Top Word Pairs in Tweet in Entire Graph Entire Graph Count
social,media 41
rt,dhirajmurthy 30
jennifer,earl 27
george,ritzer 23
rt,pjrey 19
rt,schradie 15
nathanjurgenson,2013cosm 13
media,2013cosm 12
ritzer,talking 11
talking,prosumer 9
Top Replied-To in Entire Graph Entire Graph Count
pjrey 8
nathanjurgenson 6
schradie 5
nicole_ellison 5
alexprimo 4
davidgbeer 4
stopthecyborgs 3
familyunequal 2
praxsozi 2
liamkwells 2
Top Mentioned in Entire Graph Entire Graph Count
dhirajmurthy 41
nathanjurgenson 27
pjrey 27
nicole_ellison 24
schradie 17
alexprimo 10
stopthecyborgs 8
asanews 5
jtreem 5
socialnetlab 5

 

Collaborative Organizations and Social Media

 

I am running a small conference today titled ‘Collaborative Organizations and Social Media’. The program features invited speakers Nicole Ellison (UMich), George Ritzer (UMD), Peter Gloor (MIT), and Jennifer Earl (University of Arizona). Further details of the program can be found at http://digitalcommons.bowdoin.edu/cosm/2013/program/. Slides of individual talks can be downloaded via the ‘Download’ button after you select individual papers.

We are also live streaming the event at http://new.livestream.com/accounts/3511964/events/2003155. Please feel free to participate in the event and to join the discussion via our Twitter hashtag of #2013COSM.

We will also be publishing videos of the talks on our proceedings webpage shortly.

The Great British Class Survey was undertaken by Mike Savage of the LSE and other academics at the London School of Economics, the University of Manchester, City University and the Universities of York, Bergen in Norway, and the Université Paris Descartes, France.

The survey raises important questions regarding the construction and maintenance of class in the UK.

Like others, I took the online ‘What Class Are You?’ calculator at the BBC website. It measures income variables, one’s social network, and one’s social/cultural interests.

I collected 1426 tweets from April 4 2013 – April 11, 2013 which include the URL bbc.in/12acLLV (a main URL used to link to the GBCS calculator. Some initial results of examining these data are below. Please comment on ideas for better understanding these data.

Top Hashtags in Tweet in Entire Graph Entire Graph Count
whatsyourclass 1061
britain 12
class 11
fb 5
bbc 5
elite 3
rofl 3
poorgeois 3
sociology 2
joke 2
Top Words in Tweet in Entire Graph Entire Graph Count
class 2052
new 1140
whatsyourclass 1062
system 1029
britain 1007
s 1006
group 999
m 983
out 935
found 919
Top Word Pairs in Tweet in Entire Graph Entire Graph Count
class,system 1027
new,class 1015
s,new 999
britain,s 998
group,britain 959
system,whatsyourclass 942
found,out 918
out,m 914
middle,class 426
class,group 408

I collected 1204 tweets from April 4 2013 – April 11, 2013 which include the hashtag #whatclassareyou (a key hashtag used to discuss the GBCS). Some initial results of examining these data are below.

Top URLs in Tweet in Entire Graph Entire Graph Count
http://www.bbc.co.uk/news/magazine-22000973 1117
http://www.bbc.co.uk/news/magazine-22025328 7
http://www.bbc.co.uk/news/magazine-21953364 4
http://bbc.in/12acLLV- 2
http://bbc.in/12acLLV…not 1
http://jonathancresswell.co.uk/dailymail/ 1
http://bristolaf.wordpress.com/2013/04/03/the-great-british-class-calculator/ 1
http://bbc.in/12acLLV.nokiddin 1
http://bbc.in/12acLLV.Quessed 1
http://m.bbc.co.uk/news/magazine-22000973 1
Top Hashtags in Tweet in Entire Graph Entire Graph Count
whatsyourclass 1204
britain 12
class 6
bbc 5
fb 4
elite 3
rofl 3
joke 2
sticazzi 2
in 2
Top Words in Tweet in Entire Graph Entire Graph Count
class 1502
whatsyourclass 1203
new 1129
system 1023
britain 1021
s 979
group 968
m 953
out 928
found 899
Top Word Pairs in Tweet in Entire Graph Entire Graph Count
class,system 1021
new,class 1005
s,new 975
britain,s 972
system,whatsyourclass 966
group,britain 939
found,out 898
out,m 892
class,group 399
middle,class 397

 

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