IR14 Pre-Conference Workshop Lightning Talk: Social Media Methods & Ethics

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Methodological Challenges IR14 Pre-Conference Workshop - Denver,CO [email protected] @dpwoodford Wednesday, 23 October 13

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Presented at the University of Denver, 23 October 2013.

Transcript of IR14 Pre-Conference Workshop Lightning Talk: Social Media Methods & Ethics

Page 1: IR14 Pre-Conference Workshop Lightning Talk: Social Media Methods & Ethics

Methodological Challenges

IR14 Pre-Conference Workshop - Denver,CO

[email protected]@dpwoodford

Wednesday, 23 October 13

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PLATFORMS

• Twitter: Open API, Limited on Volume, Real-Time unless paying for API; good data on user profiles.

• Facebook: Multiple levels of access; public pages easily accessible, historical data easy to obtain (unless deleted), but less precise (e.g. likes not timestamped unless page owner).

• Weibo? Vkontake? LinkedIn?

• Cost:Benefit analysis for developing infrastructure,

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TWITTER

• Streaming API is limited to ~1% of total tweets per second & Firehose access is expensive.

• Large data sets are not easily malleable, or visually analyzed (e.g. with Tableau):– Our database of Twitter users is ~3.7TB, and growing.– A weeks worth of selected TV data (current US shows) in JSON

format is 750MB, and 600MB in TSV (selected fields). And millions of rows.

• Analyzing large data sets is slow, if it’s even possible => “Usable Data”

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WHAT DOES 1% LOOK LIKE DURING SCANDAL?

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RANDOM SAMPLING VS FULL SAMPLE ANALYSIS

Source:  Tony  Hirst  (Open  University  UK)

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FULL SAMPLE, REPEATED CAPTURE

Source:  Bruns  /  Woodford  [Mapping  Online  Publics]

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ANALYSIS TOOLS: DATA ANALYTICS

• Historically @ CCI / Mapping Online Publics: .csv files, Gawk Scripts, Excel.

• Ideally: Custom Tools, R, Large Sample analysis.

• Reality: We’ve compromised on Tableau. A great option for easy data analysis, and reasonably large samples:– But still, large flat files => memory leaks (e.g. Accession charts

for Barack Obama).– Currently investigating database solutions, with mySQL as a

stop-gap.

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ANALYSIS TOOLS: CONTENT ANALYSIS

• Lots of advanced tools, but sometimes they over-complicate things; simple visuals are good for communicating to your audience..

Source:  Woodford  /  Prowd  [Fan  Cultures  and  Hatred  in  Big  Brother  15:  Race  Rows,  EliMsm  &  SporMng  Tribalism  -­‐-­‐  Forthcoming]

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ANALYSIS TOOLS: WORDLE SOMETIMES WORKS

Source:  Woodford  /  Prowd  [Fan  Cultures  and  Hatred  in  Big  Brother  15:  Race  Rows,  EliMsm  &  SporMng  Tribalism  -­‐-­‐  Forthcoming]

Wednesday, 23 October 13

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ANALYSIS TOOLS: WORDLE SOMETIMES WORKS

Source:  Woodford  /  Prowd  [Fan  Cultures  and  Hatred  in  Big  Brother  15:  Race  Rows,  EliMsm  &  SporMng  Tribalism  -­‐-­‐  Forthcoming]

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WHO’S THE AUDIENCE?

• Who you want to connect with is important in choosing methods and presentations.

• My commentary / analysis on Big Brother 15 (US) across my blog, MOP and SocialMedia@QUT was read many more times than ANY academic article I’ve ever written.

• And was picked up by industry..

• Who should we be writing for?

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ACKNOWLEDGEMENTS

• ARC Centre for Excellence in Creative Industries and Innovation (CCI) - http://www.cci.edu.au & http://www.mappingonlinepublics.net

• Social Media Research Group -- http://socialmedia.qut.edu.au

• Queensland University of Technology

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