Where do images fit in the era of ‘Big
Data’? - Analysing social media images
from a Big and small data perspective.
Farid...
READING
THE RIOTS
ON TWITTER
Rob Procter (University of Manchester)
Farida Vis (University of Leicester)
Alexander Voss (U...
What role did social media play?
2.6 million riot tweets (donated by Twitter)
–
700,000 individual accounts
Initially:
o R...
Role of Rumours
Guardian Interactive Team (Alastair Dant)
http://www.guardian.co.uk/uk/interactive/20
11/dec/07/london-riots-twitter
Data ...
Data visualizations:
what are they and what do they want?
400 million tweets/day (March 2013)
40 million Instagram images/day (January 2013)
-> 59% posted to Twitter
-> 98% posted ...
Where do images fit in the era of ‘Big Data’?
Big Data – text + number driven
Images: undervalued, underexplored
Not by the users
Big Data small data
Big Data small data
Quantitative Qualitative
Big Data small data
Quantitative Qualitative
Big Data small data
Quantitative Qualitative
WHY
Context
Context
Context
UK riots – 2.6 million tweets Egypt protest – 1FB image
READING
THE RIOTS
ON TWITTER
Rob Procter (University of Manchester)
Farida Vis (University of Leicester)
Alexander Voss (U...
The burning bus
Image sharing
2.6 million tweets: 10K unique shortened links - 19K shares
(1)image sharing platform
(2)video sharing platf...
(1) Police car (burning, attack, and aftermath)
(2) Bus (burning, aftermath, and altered image)
(3) Other Vehicle (burning...
Total image shares according to image categories
‘Although the Twitter user chose the viewing position and shared the image
through Yfrog the original image data was creat...
Deleted content
http://twitpic.com/62m6nx
The burning bus – 57 unique URLs
Image wall – ten categories
(1) The moment the bus went up in flames
(2) Smoking bus (close up of the bus, air full of thick smoke)
(3) Bus on fire (c...
Viewing within the
domestic space
Showing the first screen on the ‘second screen’
Journalists joining in
Images uploaded on Twitpic
AND Flickr using different
devices – different
audiences/users
NB riots not Instagram-ed
Was not there, claimed to be
Altered images
Tottenham as a war zone
Role of popular culture
Journalist as witness
This reminds us of the way in which John Berger notes
the significance of the act of photography in terms of
the statement...
Further work needed on how images were discussed
How to present/display the data?
Lev Manovich
Direct Visualization
Lev Manovich
http://www.manovich.net/
Aby Warburg mnemosyne
UK riots – 2.6 million tweets Egypt protest – 1FB image
Algorithmic visibility:
seeing the image through Edgerank
Finding and (re)tracing the image
Photographer of
the
images
reproduced in
Boing Boing
Photographer of
the
original image
Included in the Storyful
guidelines
for social media image
verification
Who is the
photographer?
Image altered?
Sequence o...
Verifying social media images
Where do images fit in the era of ‘Big Data’?
Big Data small data
Quantitative Qualitative
Big Data small data
Quantitative Qualitative
Big Data small data
Quantitative Qualitative
WHY
• Vis, F., Faulkner, S., Parry, K., Manyukhina, Y., & Evans, L. (in
press), ‘Twitpic-ing the riots: analysing images share...
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
Where do images fit in the era of ‘Big Data’?
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Where do images fit in the era of ‘Big Data’?

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This presentation makes an argument for a more central focus on images within social media research. It offers approaches and concrete examples from both 'Big data' and 'small data' perspectives. Presented at the Digital Transformations in the Arts and Humanities: Big Data Workshop, London, June 25 2013.

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Where do images fit in the era of ‘Big Data’?

  1. 1. Where do images fit in the era of ‘Big Data’? - Analysing social media images from a Big and small data perspective. Farida Vis, Information School University of Sheffield @flygirltwo
  2. 2. READING THE RIOTS ON TWITTER Rob Procter (University of Manchester) Farida Vis (University of Leicester) Alexander Voss (University of St Andrews) [Funded by JISC] #readingtheriots
  3. 3. What role did social media play? 2.6 million riot tweets (donated by Twitter) – 700,000 individual accounts Initially: o Role of Rumours o Did incitement take place? [no –#riotcleanup] o What is the role of different actors on Twitter?
  4. 4. Role of Rumours
  5. 5. Guardian Interactive Team (Alastair Dant) http://www.guardian.co.uk/uk/interactive/20 11/dec/07/london-riots-twitter Data Journalism Award (sponsored by Google)
  6. 6. Data visualizations: what are they and what do they want?
  7. 7. 400 million tweets/day (March 2013) 40 million Instagram images/day (January 2013) -> 59% posted to Twitter -> 98% posted to Facebook 130 million active Instagram users 16 billion images on the service 1 billion likes a day (June 2013)
  8. 8. Where do images fit in the era of ‘Big Data’?
  9. 9. Big Data – text + number driven Images: undervalued, underexplored Not by the users
  10. 10. Big Data small data
  11. 11. Big Data small data Quantitative Qualitative
  12. 12. Big Data small data Quantitative Qualitative
  13. 13. Big Data small data Quantitative Qualitative WHY
  14. 14. Context Context Context
  15. 15. UK riots – 2.6 million tweets Egypt protest – 1FB image
  16. 16. READING THE RIOTS ON TWITTER Rob Procter (University of Manchester) Farida Vis (University of Leicester) Alexander Voss (University of St Andrews) [Funded by JISC] #readingtheriots No analysis of the images circulated on Twitter
  17. 17. The burning bus
  18. 18. Image sharing 2.6 million tweets: 10K unique shortened links - 19K shares (1)image sharing platform (2)video sharing platform (3)social media platform (4)mainstream media – riot coverage (5)mainstream media – other (6)Alternative media (7)Blogs (included in Technorati top 100) (8)Blogs – other (9)Websites – news focused; (10) Websites – other (11) Spam (12) Broken link
  19. 19. (1) Police car (burning, attack, and aftermath) (2) Bus (burning, aftermath, and altered image) (3) Other Vehicle (burning, attack, and aftermath) (4) Building (burning, aftermath, before/after shots) (5) Looting (in the act, aftermath, trophy shots) (6) Screenshots (TV screens) (7) Street scenes (8) Police (9) Arrests (10) Image of text (screen grab other than TV screen, sign, newspaper front page) (11) riot clean up (12) unclear (13) Other (14) excluded (not about riots, not single still image, broken link, image removed etc.).
  20. 20. Total image shares according to image categories
  21. 21. ‘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). Re-use of images originally created by Google Streetview data collection vehicle
  22. 22. Deleted content http://twitpic.com/62m6nx
  23. 23. The burning bus – 57 unique URLs
  24. 24. Image wall – ten categories
  25. 25. (1) The moment the bus went up in flames (2) Smoking bus (close up of the bus, air full of thick smoke) (3) Bus on fire (close up of the bus, engulfed in flames) (4) Sky News – TV visible in shot (5) Sky News – screengrab (TV not visible, better quality) (6) Burning bus, police and crowds (high quality news image) (7) Bus consumed by fire (poor quality focused screengrab) (8)‘Call of Duty’ (same as smoking bus, but altered with text) (9)Aftermath (carcass of the burnt bus in close up) (10) Other
  26. 26. Viewing within the domestic space Showing the first screen on the ‘second screen’
  27. 27. Journalists joining in
  28. 28. Images uploaded on Twitpic AND Flickr using different devices – different audiences/users NB riots not Instagram-ed
  29. 29. Was not there, claimed to be
  30. 30. Altered images
  31. 31. Tottenham as a war zone Role of popular culture
  32. 32. Journalist as witness
  33. 33. This reminds us of the way in which John Berger notes the significance of the act of photography in terms of the statement: ‘I have decided that seeing this is worth recording’ (Berger, 1972, p. 179, emphasis in original).
  34. 34. Further work needed on how images were discussed
  35. 35. How to present/display the data?
  36. 36. Lev Manovich Direct Visualization
  37. 37. Lev Manovich http://www.manovich.net/
  38. 38. Aby Warburg mnemosyne
  39. 39. UK riots – 2.6 million tweets Egypt protest – 1FB image
  40. 40. Algorithmic visibility: seeing the image through Edgerank
  41. 41. Finding and (re)tracing the image
  42. 42. Photographer of the images reproduced in Boing Boing
  43. 43. Photographer of the original image
  44. 44. Included in the Storyful guidelines for social media image verification Who is the photographer? Image altered? Sequence of images around the specific image See: http://blog.storyful.com/2012/0 And more
  45. 45. Verifying social media images
  46. 46. Where do images fit in the era of ‘Big Data’?
  47. 47. Big Data small data Quantitative Qualitative
  48. 48. Big Data small data Quantitative Qualitative
  49. 49. Big Data small data Quantitative Qualitative WHY
  50. 50. • Vis, F., Faulkner, S., Parry, K., Manyukhina, Y., & Evans, L. (in press), ‘Twitpic-ing the riots: analysing images shared on Twitter during the 2011 UK riots’, in Weller, K., Bruns, A., Burgess, J., Mahrt, M., and Puschmann, C. (Eds.) Twitter and Society, New York: Peter Lang. • Vis, F. (in preparation), ‘From Egypt to Wallstreet: tracing a Facebook protest image across social media and the Internet’
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