Analyzing data from social interactions on Twitter and Facebook gives us clues as to how people choose to manage their attention. When intelligently predicted, captured and visualized, we witness emerging patterns. Some swear by a certain time of day. Others spend an inordinate amount of time trying to reach certain users deemed "influencers." But its clear that the networked dynamics at play are much more complicated. While there is no simple recipe for predicting information flows in online social spaces, there's plenty of room for optimization.

1. A Networked Take on Influence
Symposium & Workshop on Measuring Influence on Social Media | #Influence12
Social Media Lab, Dalhousie University, Halifax
Gilad Lotan | @gilgul

2. Illustra(on:
Ma.
Taylor

3. Sculpting Audiences
Alex
Dragulescu

4. Sculpting Audiences
Alex
Dragulescu

5. Influence:
The ability to disproportionately affect the spread of information
purchasing patterns of peers
television viewing behavior
Within Context => Wanted Action

6. “Influence” as an Exposed Metric is Problematic
• Simple quantifiable measure
• Innate nature
• People aren’t always rational – may trust
someone despite past transgressions
• Exogenous – may come from outside the
observed network
• Based on Context

7. Receptivity of your Audience
Flickr:
mangpages

9. f(Topic, Network, Timing, Authority, Trust, Historical Behavior,
Network Density, Activity…)

13. Given tweet(s) => if/when to post

14. Diurnal Patterns

15. Daily Routines

16. Geographic Distribution
USA
Germany
Indonesia

17. Data Reflects Us

18. Identifying Spikes
49ers:
36,
Saints:
32

19. Typical Sports Event
Game
ends!
49ers
Game
starts

20. TV
Show
Social
Movement
Awards
Ceremony

21. Breaking News (zipfian distribution)

23. Audience & Regional Trends

24. Trends by Categories
Meme
Entertainment
Lifestyle
Sports
Poli(cs
Holidays
or
Date
Place
or
Loca(on
#UglyNames
#TheDarkKnightRises
#WhenIGetDrunk
Eli
Manning
Obama
Halloween
Chilean
#truthbomb
JonahHill
#TodayImWearing
#ElClassico
StateOfTheUnion
Thanksgiving
Spain
#TextMessagesFro
#IWishIHad
Emma
Stone
mAStalker
#GoLakers
World
War
Web
9/11
Staples
Center
Edward
Scissorhands
The
Boy
is
Mine
ESPNU
Arab
Spring
Pi
Day
Wembley
#ThoughtsWheniLookI
nTheMirror
Foo
Fighters
#mydivorcesong
Giants
Won
Michele
Bachmann
Happy
Mothers
Day
Baghdad
#10ThingsIFindA.ra
c(ve

25. GeoSpan

26. Persistence
Persistence
=
A.en(on

27. Volatility (across cities)
Vola(lity
=
sum
of
edit
distance
in
consecu(ve
slots
of
the
trending
topics
list

28. Audience Attention: Real World Events
How do audiences of different clients react to real world events?

29. Networked Audiences

30. Audience Activity
@Pepsi
@AP
Pepsi
Promo(on
@AJEnglish
Whitney
Houston’s
Tragic
Death
Announced

31. Shape of an Audience
#Kony2012

32. Noblesville,
IN
Birmingham,
AL
Oklahoma
City
Engelwood,
Dayton,
OH
Pi.sburgh

33. #IGoToASchool

34. Miami

35. Vancouver

36. New Jersey

37. Teen Micro-Celebs

38. Audience Authorities
• Highly central users often have many followers
• Some people are exceptions: not that many followers, but very
central (e.g. Jezebel)
• Most valuable users to engage with? Fewer demands on
attention (less popular globally), but well-connected within
network.

39. Information Flows

44. Bridging by Providing Context

45. Instead of “Influencer”, think about:
• Deviation from the Norm
• Audience Receptivity
• Network Attributes: shape, centrality, clustering
• Bridges: generating trust
• Context Setting

46. Thank You
Gilad Lotan | @gilgul
gilad@socialflow.com