1. !"#$%‫+*! ا) ا%$#(' ا‬
Social Media A Systematic Methodology
as a Credible for Estimating the
Source Credibility of Twitter
of News? Streams
Tuesday, November 1, 11

2. !"#$%‫+*! ا) ا%$#(' ا‬
Social Media The Traditional Media has
as a Credible obviously decided to
Source classify SM as a primary
of News? source of News
Tuesday, November 1, 11

3. Tuesday, November 1, 11

4. We choose
Twitter
because:
* fastest
* most viral
* strong APIs
* extremely popular
* rising numbers
Tuesday, November 1, 11

5. Tuesday, November 1, 11

6. Tuesday, November 1, 11

7. Can we verify
the credibility
of a post?
Tuesday, November 1, 11

8. Can we verify Yes
the credibility &
of a post? NO
Tuesday, November 1, 11

9. Can we verify Yes journalistic verification methods
the credibility &
of a post? NO
Tuesday, November 1, 11

10. Can we verify Yes journalistic verification methods
the credibility &
of a post? NO “cannot be verified independently”
Tuesday, November 1, 11

11. Nevertheless ...
The Media tries to
verify the credibility
of posted stories?
Tuesday, November 1, 11

12. ➡ great deal of experience
The ➡ the sheer volume of tweets
Verification is time consuming
Process ➡ hard to quickly identify a
is Difficult & scoop
very time ➡ technical limitations
➡ inefficient twitter search
consuming ➡ inefficient refresh rate
Tuesday, November 1, 11

13. Tuesday, November 1, 11

14. What we 100s - 1000s of tweets
being filtered automatically
want to offer from noise through a
the media preselection process
Tuesday, November 1, 11

15. Tuesday, November 1, 11

16. What is the 1. Understanding how
Automated people evaluate tweets
individually
Preselection 2. Adding metrics to the
Process evaluation
Based on? 3. Applying probability
algorithms
Tuesday, November 1, 11

17. 1. Understanding how people evaluate tweets individually
as individuals we want to:
Why Do People ➡ to post only true stories
Evaluate ➡ to retain or grow our
follower-ship
Users in the ➡ remain popular
First Place? ➡ be seen as an authority
Tuesday, November 1, 11

18. 1. Understanding how people evaluate tweets individually
we analyze the ...
How do we as ➡ user
individuals ➡ community
➡ interaction
evaluate ➡ attitude / typical behavior
tweets? ➡ set of morals
➡ topics
➡ influence
Tuesday, November 1, 11

19. 1. Understanding how people evaluate tweets individually
What is the
result of We want to identify if a user
evaluating an is qualified to make the
statement just posted.
individual?
Tuesday, November 1, 11

20. Tuesday, November 1, 11

21. 1. Understanding how people evaluate tweets individually
The more influential a user
Our Thesis the higher the probability
(part one): that news posted by this
user is credible
Tuesday, November 1, 11

22. 2. Adding metrics to the evaluation
Evaluation ➡ Klout
The community around the
metrics user and the interaction with
this community: number of
followers, their influence,
pro users mentions, retweets ...
also check ➡ Peerindex
social influence The topics the user usually
tweets, the topics of the
services community around the users,
the topics of conversations
Tuesday, November 1, 11

23. 2. Adding metrics to the evaluation
➡ They have limitations
Are these ➡ They have flaws
services ... but
reliable? ➡ They supply an excellent
probability value / index
Tuesday, November 1, 11

24. 2. Adding metrics to the evaluation
Tuesday, November 1, 11

25. 2. Adding metrics to the evaluation
Can We
Measure
Tuesday, November 1, 11

26. 2. Adding metrics to the evaluation
Can We
Measure
Credibility?
Tuesday, November 1, 11

27. 2. Adding metrics to the evaluation
Can We
➡ Credibility itself: NO
Measure ➡ Probability: YES
Credibility?
Tuesday, November 1, 11

28. 3. Applying probability algorithms
➡ take their twitter seriously
➡ feel responsible about
posting and reposting true
Tweet stories
Propagation ➡ act as an evaluation point
There is clear in the propagation of a
indication that story
influential users: ➡ increase the probability
of a story being true by an
measurable increment
Tuesday, November 1, 11

29. 3. Applying probability algorithms
The more influential the user
Our Thesis the higher the probability
(part two): that news posted by this
user is credible
Tuesday, November 1, 11

30. 3. Applying probability algorithms
Tweet Propagation
✜ ✜✜ ✜✜✜
This schematic is ridiculously over simplified.
The true probability increase will be based on
probability theory algorithms
Tuesday, November 1, 11

31. twitter stream
Our Proposed
System Will Offer an
Alternative View of
the Twitter Stream
Tuesday, November 1, 11

32. probability value on top of the twitter stream
✜
✜✜
Our Proposed
System Will Offer an
Alternative View of ✜✜
the Twitter Stream
✜✜✜✜
Tuesday, November 1, 11

33. probability value on top of the twitter stream
✜
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Our proposed ✜✜✜✜
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System Will Offer ✜✜✜
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a Novelty! ✜✜
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The Credibility INDEX ✜✜
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Tuesday, November 1, 11

34. probability value on top of the twitter stream
✜
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The Media Now ✜✜✜✜
Have Dozens Instead of ✜
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100s-1000s to ✜✜
Attempt to ✜✜
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Verify Independently ✜✜
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Tuesday, November 1, 11

35. Thank You
Tuesday, November 1, 11