1. social media:
the good, the bad and the ugly
Josh Cowls
Oxford Internet Institute

2. the internet: an Information and
Communications Technology

3. the internet: an Information and
Communications Technology

4. the internet: an Information and
Communications Technology

5. the internet: an Information and
Communications Technology

6. social media: platforms that facilitate
information and communication over the
internet

7. social media: platforms that facilitate
information and communication over the
internet
… of different sorts, to varying degrees …

8. For the collection and diffusion of
information, social media can be a
revolutionary social good

9. Example: Miracle on the
Hudson
the tweet that ‘made’ Twitter

10. Example: Flowminder
• Haitian earthquake struck in 2010 -> led to mass migration away
from capital Port Au Prince.
• Flowminder Foundation asked for phone records of Haitians to
show location of calls from 1.9 million SIM cards over 200 days.
Data used to estimate movement of people around the country,
aiding disaster relief.
• These estimates of geographical distribution of people across Haiti
were later shown to match well to estimates from a large
retrospective UNFPA household survey.Bengtsson L, Lu X, Thorson A, Garfield R, von Schreeb J. (2011). Improved Response to Disasters and Outbreaks by Tracking Population
Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti. PLoS Med 88: e1001083.

11. Example: Ushahidi
• Ushahidi is a nonprofit technology development company which develops
free and open source software for information collection, aggregation and
visualisation.
• Stop Stock-Outs is a campaign to ensure access to essential medicines by
using Ushahidi and Frontline SMS to map the availability of essential
medicines at public health facilities in several African countries. These are
medicines used to treat common diseases such as malaria, pneumonia,
diarrhoea, HIV, TB and diabetes.
• Researchers visit public health institutions countrywide and check on the
availability of a list of 10 essential medicines. These are medicines that
should be readily available in public health facilities.
• The researchers then report on the results through short messaging
Bellagio Big Data Workshop Participants. (2014). “Big data and positive social change in the developing world: A
white paper for practitioners and researchers.” Oxford: Oxford Internet Institute. Available online:
http://www.rockefellerfoundation.org/uploads/files/c220f1f3-2e9a-4fc6-be6c-45d42849b897-big-data-and.pdf .

12. These examples used social media
technologies (SMS, ‘wiki’-style websites) –
but the data were collected either passively
and tacitly (Flowminder) or in a structured,
formulaic way (Stop Stock-Outs)

13. When information is more mediated:
1. we can be very anti-social
2. offline hierarchies and inequalities can
replicate
3. behaviour is harder to measure

14. When information is more mediated:
1. we can be very anti-social
2. offline hierarchies and inequalities can
replicate
3. behaviour is harder to measure

15. anti-social media

16. anti-social media
Retweet network of political communication on Twitter.
Red cluster: 93% right-leaning users
Blue cluster: 80% left-leaning users
M. D. Conover, J. Ratkiewicz, M. Francisco, B. Gonc¸alves, A. Flammini, F. Menczer, ‘Political
Polarization on Twitter’, presented at ICWSM 2011

17. anti-social media
Release of celebrities’ private photos
“I didn't take the money and run. S**t got weird once I
started posting samples. … People wanted s*** for free.
Sure, I got $120 with my bitcoin address, but when you
consider how much time was put into acquiring this stuff
(i'm not the hacker, just a collector), and the money (i
paid a lot via bitcoin as well to get certain sets when this
stuff was being privately traded Friday/Saturday) I really
didn't get close to what I was hoping.”

18. anti-social media

19. anti-social media
the core problem: the internet doesn’t
discriminate

20. When information is more mediated:
1. we can be very anti-social
2. offline hierarchies and inequalities can
replicate
3. behaviour is harder to measure

21. hierarchical or horizontal?

22. hierarchical or horizontal?
in theory

23. hierarchical or horizontal?
in theoryin reality

24. hierarchical or horizontal?
Kwak et al 2010:
• Low reciprocity: only 22.1% of dyads are
reciprocal
• Offline celebrities are most followed on
Twitter
Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon. What
is Twitter, a Social Network or a News Media? Proceedings of the 19th
International World Wide Web (WWW) Conference, April 26-30, 2010,

25. Example: trolling celebrities
Even the ugliest of behaviour is based on
network effects

26. Example: Twitter during #PMQs
• Old media elites on new media platforms
• The difference between speaking and
being heard
• Research questions:
– Who were the most-followed users active during
the debates?
– Were they media elites or from outside the
traditional mainstream?
– Were non-mainstream voices rebroadcasted by
elites through the use of retweets or links?

27. Example: Twitter during PMQs
The mass media still hold
sway,
but with a diluted reach
24/04/13, #PMQs
The mass media seldom incorporated
outside voices
a) By using the retweet function infrequen
0.00%
20.00%
40.00%
60.00%
Media elite Political elite Others
Percentage of tweets that
were retweets
b) By mostly retweeting each othe
Who did media elites retweet?
Other media
elites
Political elites
Others

28. Example: los indignados
Gonzalez-Bailon, S., Borge-Holthoefer, J. and Moreno, Y. (2013) Broadcasters and Hidden Influentials in
Online Protest Diffusion. American Behavioral Scientist. doi:10.1177/0002764213479371

29. When information is more mediated:
1. we can be very anti-social
2. offline hierarchies and inequalities can
replicate
3. behaviour is harder to measure

30. not made to measure
The messier the data, the harder to measure

31. Example: using social media to
measure public opinion
Cost
Utility
Big data model
Standard sample survey Social media analysis

32. Example: using social media to
measure public opinion
But challenges remain:
Representativeness
Reliability
Replicability
≠

33. Example: mapping tweets during
Hurricane Sandy
Shelton, T et al, ‘Mapping the data shadows of Hurricane Sandy: Uncovering the
sociospatial dimensions of ‘big data’. Geoforum Volume 52, March 2014, pps 167-79

34. Example: indyref on Facebook
“To produce the report, Facebook chose a
basket of phrases that represented the Yes
campaign, and another set that represented
Better Together. Each mention of these
phrases, by anybody using Facebook, counted
towards their respective totals.”
The data makes no distinction between posts
in favour of a particular phrase, and those
which denigrate it. If someone posted "Let's get
behind 'Yes Scotland'", a friend liked it, another
shared it, and a third commented "I agree, I'm
voting Yes", four interactions were added to
Facebook's Yes tally. Equally, a user who
posted "I can't bear 'Yes Scotland'" - with
friends who liked, shared and commented in
agreement - had exactly the same impact on
the statistics.
Facebook also reports that "in personality
politics, Salmond has a decisive victory over
Darling". The leader of the Yes campaign has
prompted 700,000 interactions, whereas the
leader of Better Together has prompted
250,000. Here, the firm compiled the figures in
a similar way, counting the number of times

35. When information is more mediated:
1. we can be very anti-social
2. offline hierarchies and inequalities can
replicate
3. behaviour is harder to measure

36. When information is more mediated:
1. we can be very anti-social
2. offline hierarchies and inequalities can
replicate
3. behaviour is harder to measure
…but…

37. The data remains hugely powerful, for those
who have it

38. “In God we trust…

39. “In God we trust…
… all others bring data”
W. Edwards Deming

40. Example: using Facebook to
influence emotions
700,000 users were exposed to slightly
more negative or slightly more positive
content in their news feed, which changed
their own posting behaviour.
http://www.pnas.org/conte
nt/111/24/8788.full

41. Example: using Facebook to
encourage people to vote
“A randomized controlled trial of political mobilization
messages delivered to 61 million Facebook users during the
2010 US congressional elections. The results show that the
messages directly influenced political self-expression,
information seeking and real-world voting behaviour of millions
of people. Furthermore, the messages not only influenced the
users who received them but also the users’ friends, and
friends of friends.”
Robert M. Bond, Christopher J. Fariss, Jason J. Jones, Adam D. I. Kramer. Cameron Marlow, Jaime E. Settle & James H. Fowler. A 61-million-
person experiment in social influence and political mobilization Nature 489, 295–298 (13 September 2012) doi:10.1038/nature11421

43. social media (meta)data +
algorithms =

44. Example: Chicago’s ‘predictive
policing’
“When the Chicago Police Department sent one of its
commanders to Robert McDaniel’s home last summer, the 22-
year-old high school dropout was surprised. Though he lived in a
neighborhood well-known for bloodshed on its streets, he hadn’t
committed a crime or interacted with a police officer recently. And
he didn’t have a violent criminal record, nor any gun violations.
Yet, there stood the female police commander at his front door
with a stern message: if you commit any crimes, there will be
major consequences. We’re watching you.
What McDaniel didn’t know was that he had been placed on the
city’s “heat list” — an index of the roughly 400 people in the city of
Chicago supposedly most likely to be involved in violent crime.”

46. Summary
1. For the collection and diffusion of
information, social media can be a
revolutionary social good
2. When information is more mediated:
• we can be very anti-social
• offline hierarchies and inequalities can replicate
• behaviour is harder to measure
3. The data remains hugely powerful, for
those who have it

47. @JoshCowls