ESRC Research Methods Festival - From Flickr to Snapchat: The challenge of analysing images on social media

Researcher at University of Sheffield (Information School)
Jul. 9, 2014

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ESRC Research Methods Festival - From Flickr to Snapchat: The challenge of analysing images on social media

  1. From Flickr to Snapchat: The challenge of analysing images on social media Farida Vis, Information School University of Sheffield @flygirltwo
  2. Images posses the ability to grab our attention
  3. Social media companies know this
  4. Images are key to engagement
  6. Camera: used to be for special occasions Smartphone: always with us
  7. Everyday snaps Witnessing events
  8. US 65% smartphone penetration Smartphones overtaken desktop usage to access the internet Mobile internet accounts for majority of internet use in US (57%) Users typically access the internet via apps on mobile devices All figures from comScore, US Digital Future in Focus, 2014
  9. UK: The over-55s will experience the fastest year-on-year rises in smartphone penetration. Smartphone ownership should increase to about 50% by year-end, a 25% increase from 2013, but trailing 70% penetration among 18-54s. The difference in smartphone penetration by age will disappear, but differences in usage of smartphones remain substantial. Many over 55s use smartphones like feature phones. All figures from Deloitte, predictions for 2014
  10. Rise of platforms and apps focused on visual content Pinterest Tumblr Instagram Vine Snapchat ‘Mobile first’ –> ‘… and only’ | simple easy, user friendly design
  11. Facebook daily image uploads: 350 million (November 2013) Instagram daily image uploads: 60 million (March 2014) Twitter: 500 million tweets daily (March 2014) Snapchat daily snaps: 400 million (November 2013)
  12. Images largely ignored in social media research Not easy to ‘mine’ Hard to figure out meaning Huge interest in industry
  13. Images in crisis communication
  14. Social Reading the Riots, 2011 Social Users debunking rumours
  15. Image sharing during the 2011 UK riots
  16. ‘Although the Twitter user chose the viewing position and shared the image through Yfrog the original image data was created by one of Google’s ‘numerous data collection vehicles’ using their R5 ‘panoramic camera system’’ (Anguelov et al., 2010, pp. 32-33).
  17. The burning bus: 57 unique URLs
  18. Hurricane Sandy Image sharing practices during crises: fakes
  19. #FakeSandy pics 250,000 tweets (4hrs) 1 weekend ‘fakes’ What is shared by locals vs wider social media audiences/users? Where in the ‘long tail’ might we find useful information? Most visible most valuable≠
  20. Hurricane Sandy images • Fake as in Photoshopped • Fake as in still from Hollywood disaster movie • Fake as in not what we think we’re looking at • Perceived fake, but in fact real • Intensions of users? What do we think they are doing?
  21. "Picturing the Social: transforming our understanding of images in social media and Big Data research.” ESRC Transformative Research grant
  22. Farida Vis (PI) – Media and Communication Simon Faulkner – Art History/Visual Culture James Aulich - Art History/Visual Culture Olga Gorgiunova – Software Studies/Sociology Mike Thelwall – Information Science/software Francesco D’Orazio – Industry/Media/software + Research Associate – Digital Ethnography
  23. “Qualitative data on a quantitative scale” (D’Orazio, 2013)
  24. Traditional broadcasting model Production of message Message = text Reception of the message
  25. Building new theory and method Structures Users Content
  26. Structures Users Content
  27. How do social media companies make images visible?
  28. Address the quantitative magnitude and the qualitative intensity of social media image production and circulation
  29. • Screen Shot 2014-07-09 at 06.05.51
  30. Doing interdisciplinarity
  31. Images shared on Twitter (natively uploaded) around the death and funeral of Margaret Thatcher 150,000 tweets 17,000 different images
  32. Seeing like software/like a human How are images sorted and organised? How do we select what to look at? How do these images circulate/ Where have they come from? How do we (re)present them?
  33. Direct Visualisation/Lev Manovich
  34. Aby Warburg’s mnemosyne
  35. @VisSocMedLab @flygirltwo