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Interoperability of
a Social Media Observatory
Karissa McKelvey
And Filippo Menczer
Center for Complex Networks and Systems Research
School of Informatics and Computing
Indiana University, Bloomington
1
truthy.indiana.edu 2
Can we use social media as
laboratories for social
science?
truthy.indiana.edu 3
Political Polarization on Twitter Michael Conover, Jacob Ratkiewicz, Bruno Gonçalves, Alessandro Flammini
& Filippo Menczer International Conference on Weblogs and Social Media 2011
truthy.indiana.edu 4
Competition for attention
Competitions among topics in a world with limited attention Nature Scientific
Report, 2012. Lilian Weng, Alessandro Flammini, Alessandro Vespignani and Filippo
Menczer.
#jan25
truthy.indiana.edu 5
truthy.indiana.edu 6
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0 20 40 60 80 100
−2e+050e+002e+05
a. 2010
Tweet Share
VoteMargin
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0 20 40 60 80 100
−2e+050e+002e+05
b. 2012
Tweet Share
VoteMargin
More Tweets, More Votes
DiGrazia, Joseph, McKelvey, Karissa, Bollen, Johan and Rojas, Fabio. More Tweets, More Votes: Social
Media as a Quantitative Indicator of Political Behavior (February 21, 2013). Available at SSRN:
http://ssrn.com/abstract=2235423 or http://dx.doi.org/10.2139/ssrn.2235423
astroturf
truthy.indiana.edu 7
Data “mine” ing
truthy.indiana.edu 8
Data “ours” ing
truthy.indiana.edu 9
truthy.indiana.edu
truthy.indiana.edu 10
truthy.indiana.edu 11
Infrastructure
nosql& mysql&hbase&
Storage&
Social&
Media&
Model& APIs&
Toolkits/
Website&
truthy.indiana.edu 12
Infrastructure
nosql& mysql&hbase&
Storage&
Social&
Media&
Model& APIs&
Toolkits/
Website&
truthy.indiana.edu 13
Data Collection
• Twitter Streaming API
• August, 2010 – present
• 5TB Compressed
truthy.indiana.edu 14
Real-Time Filtering
• Past 90 days
• US Politics 2012, Social Movements, News
• MySQL database + website
truthy.indiana.edu 15
Infrastructure
nosql& mysql&hbase&
Storage&
Social&
Media&
Model& APIs&
Toolkits/
Website&
truthy.indiana.edu 16
Model
• Events
– Post on a social media site
• Users
– Actors in the post
– Sender, receiver, forwarder, etc
• Meme
– Discernable unit of information transfer
truthy.indiana.edu 17
Meme
Hashtag
User
URL
Phrase
truthy.indiana.edu 18
Building the Network
truthy.indiana.edu 19
Retweet (forward) Mention (conversation)
celebrities
spam
astroturf
politics
20
politics
truthy.indiana.edu 21
#tcot
truthy.indiana.edu 22
celebrities
politics
truthy.indiana.edu 23
@barackobama
truthy.indiana.edu 24
celebrities
spam
astroturf
politics
25
@bek_rt
truthy.indiana.edu 26
Infrastructure
nosql& mysql&hbase&
Storage&
Social&
Media&
Model& APIs&
Toolkits/
Website&
truthy.indiana.edu 27
truthy.indiana.edu
truthy.indiana.edu 28
truthy.indiana.edu 29
Infrastructure
nosql& mysql&hbase&
Storage&
Social&
Media&
Model& APIs&
Toolkits/
Website&
truthy.indiana.edu 30
API & Website
• Filterable and searchable interface to find
memes of interest
• Endpoints for users to access data
programmatically
• Visualizations (saw earlier)
truthy.indiana.edu 31
Further Thoughts
• Potential uses:
– Pedagogy
– Prototyping
– Research
• Terms of Service
– Tweet text
– Derived Data
truthy.indiana.edu 32
Thanks
Papers at cnets.indiana.edu/groups/nan/truthy
Sandro Flammini
Bruno Conçalves
Jacob Ratkiewicz
Lilian Weng
Mike Conover
Johan Bollen
Przemek Grabowicz
Mark Meiss
Alex Vespignani
Alex Rudnick
Luca Aiello
Filippo Menczer
truthy.indiana.edu 33

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Interoperability of a Social Media Observatory

Notas del editor

  1. When people communicate online, they leave digital tracesWith easy access to the data we create on social media, social scientists can study human social behavior on a larger scale than has ever been possible in human history.
  2. Are there well-defined communication behaviors that characterizethe activities of influential actors?What is the role of bridging users in facilitating informationtransfer between ideologically opposed communities?Who are the opinion leaders, and how dothey engage in frame-making and agenda-setting?
  3. The polarization of political communities
  4. The evolution of memes
  5. Meme DetectionStatic & Interactive VisualizationsData downloads
  6. Bundle each event, in this case a tweet, into groups based on common features.
  7. Connect the users that communicate
  8. visualizations of social media communication which can show us the network topology.Each person is represented by a nodeA line represents an information transfer between those two peopleOrange lines are mentions, and blue lines are retweetsThe width of the edge is a measure of the strength of that relationship; computed by how many events of that type occurred between those two peopleWe can see different characteristics in these networks for different types of communication. A network centered around a celebrity like Barack Obama , for example, has thousands of people mentioning and retweeting that person. A meme that is propagated by spammers will look much different, for example when a few users constantly retweeteachother
  9. The meme is the account in the center. A bunch of accounts collude by retweeting each other (as displayed by the thick blue edges) to promote a particular website
  10. Meme DetectionStatic & Interactive VisualizationsData downloads