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This week, I have been invited to be a guest on Laurie Taylor’s BBC Radio 4 Program Thinking Allowed to talk about my book, Twitter: Social Communication in the Twitter Age (Polity Press). The BBC has kindly linked to my blog and I thought I would blog some quotes from the book that can both serve as talking points, but also a way in which to stimulate critical discussion of Twitter (via my blog’s comment space at the bottom of the page).  Twitter is at a particularly formative time as the company is gearing up for a initial public offering on the NASDAQ of ~ $20 billion. I look forward to comments as well as tweets directed to @dhirajmurthy.

Selected quotes from Twitter: Social Communication in the Twitter Age (Polity Press):

“…like a radio, a user’s Twitter timeline could be playing in the background and if the user becomes interested in a particular story, Twitter moves from the ambient periphery to the active center”

“The ability to tweet and post YouTube videos of your “disaster experience” has the potential for normally marginalized individuals and groups to update the world about their situation”

“Hashtag categories illustrate the ability of Twitter to be both an individual and communal news space simultaneously”

“Twitter is not displacing traditional media… [and] news organizations have found the medium useful in their coverage of breaking news”

“Phantom’ Twitter accounts…post banal information with a trending hashtag to dilute activist hashtags”

“Twitter and Facebook… lend themselves to being used by authorities to ‘spy’ on activists”

“‘Citizen-journalists,’ non-professional journalists, are taking pictures from their smartphones and embedding them in tweets, and this material has now become part of some journalists’ source mix.”

“much of the talk on Twitter is monological, or just never listened to or responded to”

“it is impossible to monitor the integrity of information on Twitter”

“Twitter’s citizen journalism is not exempt from the hierarchies endemic in traditional media industries. Rather, new forms of elitism are emerging”

“tweets regarding breaking news, disasters, and public health epidemics can be misleading, incorrect, or even fraudulent”

”Tweets are analagous to bees in that they exist both as individuals and as part of a collectively built whole”

“Twitter in some ways has redefined existing cultural practices such as diary keeping, news consumption, and job searching”

“Twitter works…because [you] stop thinking about what you’re revealing and who’s on the other end.”

“Twitter has not determined social sharing across great distances, but has facilitated already emergent shifts in social behaviors.”

“If a tweet is retweeted often enough or by the right person(s), it gathers momentum that can emulate a snowball effect”

“Twitter enables users to wear two hats of producer and consumer.”

“even if the audience is not “obvious or apparent,” that does not translate to an absence of an audience with tweets disappearing into the ether”

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]

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

 

 

I have been avidly watching election-related tweets yesterday and today. In both my classes today, I included discussions of tweets which either mentioned Obama, Romney, #election2012, and #election2012 America. The latter was particularly useful in highlighting tweets from non-American tweeters. Supporting the idea that Twitter functions like a diary or chronicle of one’s daily life are tweets which inclue “I just voted”, “just voted”, or “on my way to vote”.

Some interesting tweets which emerged from both my searching and that by students are:

  • NBC confirms a voting machine malfunctioning, changing votes for Obama to Romney in Pennsylvania http://soup.ps/RDBbH1

[Unsurprisingly, tweets recirculating news stories have been extremely popular today. Engagement by the public with news or even with campaigns via social media is noted as significant by Himelboim (2012)]

  •  if Obama loses because y’all dumbass are posting your ballots on social networks, your ass shouldn’t have the privileges to vote!

[The interesting trend of voters using their smart phones to take pictures of their ballots and post them on social media supports arguments in the literature which discuss how ubiquitous computing makes it possible for us to increasingly publish things which are normally very much in our private sphere. Instagramming one’s ballot seems particularly popular!]

  •  ⬜ Romney ⬜ Obama ✔ Glitter, Victoria’s Secret, and tiaras.

[The ‘third option’ genre of tweets has been used frequently within the #election2012 hash tag]

  •  I’ve been praying all day for a #Romney victory

[Tweets in the hash tags provide empirical support that the religious right is actively engaged within Twitter. This supports findings in the literature of the conservative movement’s use of digital media technologies (Bennett 2012)]

[Interestingly, Paul McCartney’s tweet was the most retweeted #election2012 tweet at one point today (#beatles #ukinvasion) ;)]

  • Whether you vote Republican, Democrat or 3rd Party, you should still celebrate with @(name of brand) #America #election2012

[Unsurprisingly, lots of businesses, brands, and bands are using the #election2012 hash tag for promotion purposes. The use of hash tag manipulation is discussed by Page (2012)]

 References:

1.            Page, R., The linguistics of self-branding and micro-celebrity in Twitter: The role of hashtags. Discourse & Communication, 2012. 6(2): p. 181-201.

2.            Bennett, W.L., The Personalization of Politics: Political Identity, Social Media, and Changing Patterns of Participation. The ANNALS of the American Academy of Political and Social Science, 2012. 644(1): p. 20-39.

3.            Himelboim, I., et al., Social Media and Online Political Communication: The Role of Interpersonal Informational Trust and Openness. Journal of Broadcasting & Electronic Media, 2012. 56(1): p. 92-115.

While I was writing my book about Twitter (Twitter: Social Communication in the Twitter Age), I took an interest in tracking the US Republican primary as it was being constructed within Twitter. Last year, I started collecting all geo-located tweets  (tweets with location information turned on) for the 50 most populous urban American cities (according to U.S. Census statistics ). Because of the geographical richness of this data set, I thought it would be a perfect source to use to study twitter activity surrounding the US Republican primary. Working with  Alexander Gross and Stephanie Bond, I designed and developed a tool to visualize this specific geographically-anchored landscape.

The 2012 US presidential election provided another opportunity to leverage this data. Twitter has been extremely active in terms of election-related discourse. Our Election 2012 Twitter Visualization Tool uses emergent big data research methodologies to visualize the election. The visualization tool has been optimized for the Safari browser (and is known to have some issues in other browsers).

The goal of our research is to explore urban American responses to the 2012 presidential candidates on Twitter. In order to create a representative sample of tweets from urban centers in the United States, we collected tweets from Twitter by location. We took the 50 most populous American cities according to the U.S. Census and instructed Twitter to send us tweets that were within 7-12km of the locations of these cities.

Our software collects these geo-located tweets and uses the data to chart the relative buzz surrounding candidates in the 2012 presidential election. The tool charts the relative popularity of each primary candidate as measured by the number of tweets which we have collected over the last 24 hours and identified with a particular candidate. For a tweet to be counted as referring to a particular candidate, the tweet must contain the candidate’s first and last name separated by a space e.g. “Mitt Romney” or the candidate’s official campaign twitter account name or the account name eg @mittromney. A single mention as reported by the chart’s dynamic legend is equivalent to one tweet which contains one of the candidate names. Tweets which contain more than one candidate name will be counted as mentions for both candidates. These stringent rules prevent unecessary possible over counting of tweets for a candidate. Though the frequency of the tweet count in our visualization is low because of this, the data collected is very robust. Specifically, all tweets visualized do refer to Obama or Romney.

Please visit the tool’s webpage at my lab, the Social Network Innovation Lab, for more detailed information.