1. Definition of Criteria for Impact Analysis
A work in progress
Christoph Fuchs

2. Overview What I won't talk about Twofold
Classical social network analysis
Criteria in the online world
Specific definition of criteria
Open questions

3. I will not talk about impact in the "real world"!
What kind of impact?
I will not talk about impact in the "real world"!
Such as...
Total revenue
Offline bookings
Offline sales
...

4. What I will talk about
Impact of actors and shared items on online social platforms.
Looking for impact criteria which are
accessible (via automatic retrieval)
independent of platform specifics

5. Impact analysis is twofold
Two kinds
Impact analysis is twofold

6. Two kinds of impact analysis
actor level (potential impact)"Who is the most important guy?"

7. Two kinds of impact analysis
item level (impact after publication)"What is 'hot' right now?"

8. In other terms = page post
Impressions"...measure the number of times a post from your Page is displayed, whether the post is clicked on or not."
Reach"...measures the number of people who received impressions of a Page post."

9. "Classical" vs. "Online" Classical social network analysis
actor centric
Online impact analysis
item centric

10. Classical Social Network Analysis
aka Graph Theory

11. Measures from "classical" Social Network Analysis
All* classical approaches are on the actor level.
Centrality
Prestige
described by Wasserman and Faust in 'Social Network Analysis'
Stanley Wasserman: University of Illinois, US
Katherine Faust: University of South Carolina, US
* at least all I have found so far.

12. Who is the "most important guy"?

13. Centrality Centrality measure C(actor) = [0 .. 1]
Normalized on the graph size.
Online: Where does your graph end?

14. Centrality Degree Centrality"Who has the most ties to other actors?"
Closeness Centrality"How close is an actor to all the others?"
Betweenness Centrality"Interactions between two nonadjacent actors might depend on the other actors in the set of actors, especially the actors who lie on the paths between the two."

15. Degree Centrality "Who has the most ties to other actors?"
Cdinbound(orange) = 4 [normalized: 4 / 5 = 0.8]
Cdoutbound(orange) = 3 [normalized: 3 / 5 = 0.6]
Cdoutbound(green_women) = 0.2

16. Closeness Centrality "How close is an actor to all the others?"
Online problem: Where does your graph end?
Relevant for the online world?

17. Betweenness Centrality
"Are you between any important actors?"
Online problems
- Mostly direct communication (to immediates) - Distance can be easily reduced to 1

18. Prestige Degree PrestigeIndegree of each actor.
Proximity PrestigeBased on average distance of actors in an influence domain.
Status or Rank Prestige"If one’s influence domain is full of prestigious actors, one’s prestige should also be high. If, however, an actor’s domain contains only peripheral, or marginally important, actors, then the rank of this actor should be low."

19. Criteria
in the online world

20. Criteria? Connections between actors May be directed connections
Indegree of connections
Outdegree of connections

21. Criteria? Connections translated in terms of social platforms
Facebook: x is a friend of y
Twitter: x is following y
YouTube: x subscribed to y
...

22. Criteria? There may be different types of connections
A platform may support
Some kind of friendship relation
Some kind of subscriptions
...

23. Platform specific criteria
Some platforms have a form of reputation measurements

25. Item level "How many people have seen it?"
"How many people have clicked on it?"

26. Item level
"How many people have reacted on it? And how did they react?"
Like (+1, thumbs up, ...)
Favourite
Reply or comment
"How many people have re-shared it?"

27. Criteria? All kinds of criteria... Views and clicks Unary feedback
Binary feedback
Ratings
Re-publication

28. Criteria? ... and more Replies (may not be text) Comments
Sentiment of comments

29. Criteria? Platform specific examples MoodsDeviantART
Bumpingvarious Forums
Pull Requests, Forks, Watches github
...

30. So many things to measure!
What to make of it?
So many things to measure!

31. We need impact criteria which are accessible
independent of platform specifics

32. Actor level criteria Connections between actors
May be directed connections
in- and outdegree of connections

33. Actor level criteria Criterion (#) Value
Actors who are friends with you
Integer
Actors whom you are friends with
Actors who want to be friends with you [*]
Actors you want to be friends with [*]
Actors subscribed to your stream ("following" you)
Actors to whom you are subscribed
Reputation score [?]
[*] Are those important?
[?] Not sure about available reputation scores - platform dependency.

34. Item level criteria Criterion (#) Value Views Integer Clicks
Positive unary feedback
Special unary feedback
Negative unary feedback
Re-publications
Replies
Comments
Integer / Text
Sentiment
Hash with Integer

35. Open Questions
...or "Problems"

36. Open questions What about re-publications?
broadens the 'impact area'
you don't have access to data outside your immediate peers
It may be important who re-published it.
Almost impossible to measure how many times an item has been viewed if it goes viral.

37. Open questions Is normalization important? Normalization
Usually dependent on graph size
Online social network graphs are huge!

38. Open questions Is the actor's reputation important? What about...
the success of previously published items?
the sentiment of previously published items?
Is any publicity good publicity?

39. Re-publication >? Like
Open questions
Weighing
What criteria are the most important?
Re-publication >? Like
Combination across platforms
One platform may only have 'Like'
Online social network graphs are huge!

40. Open questions Algorithm? To be investigated...
Can existing classical approaches be used?
Existing open-source algorithms?
Is performance important?
To be investigated...

41. Thank you.
Questions? Discussion!