This document summarizes a study analyzing how bursts of activity diffuse across the hyperlink network on Wikipedia following major events, using the 2013 Boston Marathon bombings as a case study. The study finds that bursts of editing activity on articles are correlated with developments in the real world and that information seeking drives the creation of new articles and relationships between articles. Future work could further analyze how bursts diffuse through the larger hyperlink network and use textual features to predict bursts of activity.

1. Ripples on the Web:
Diffusion of Activity Bursts across
Hyperlink Networks in Wikipedia
Brian Keegan (@bkeegan)
Yu-Ru Lin (@rhodiuslin)
David Lazer (@davidlazer)
Sunbelt XXXIII
Hamburg, Germany
May 23, 2013

2. 2

3. Theoretical motivations
• Information seeking and sense-making
• What kinds of information is general population
seeking following disaster?
• Mass convergence and crisis informatics
• What implications does rapidly emerging information
have for emergency responders?
• Networks of knowledge and collaboration
• How is this information verified and synthesized?

4. Twitter basically sucks
• Information seeking and
sense-making
• More noise & echo than
signal, fragmented behavior &
commons
• Mass convergence and crisis
informatics
• Sampling & temporal censoring
• Networks of knowledge and
collaboration
• Unverifiable, misinformation, non-
cumulative

5. Wikipedia basically rules
• Information seeking and
sense-making
• Existing repertoires & activity
around contextual information
• Mass convergence and crisis
informatics
• Fine-grained & accessible history
• Networks of knowledge and
collaboration
• Cited, debated, and cumulative
account

6. Networks from Wikipedia data
• Markup
• Hyperlinks: i has a link to j
• Revisions
• Coauthorship: i shares an
editor with j
• Pageview activity
• Correlation: i’s pageviews
correlated with j

7. Case study
7

8. Case study
• Boston Marathon bombings
• Two distinct dates for burst of activity
related to major developments:
• April 15: Bombing
• April 19: Manhunt
• New information  new articles bursting

9. Article dynamics – First 3 weeks
9

10. Dynamics – First 18 hours
10

11. Pageview dynamics

12. Pageview and editing coupling

13. Pageview and editing coupling

14. 14
HYPERLINK NETWORK

15. Types of networks
• Markup
• Hyperlinks: i has a link to j
• Revisions
• Coauthorship: i shares an editor with j
• Pageview activity
• Correlation: i’s pageviews correlated with j

16. 16
Boston
Marathon
bombings
Boston
Marathon
Watertown,
Mass.
Boston, M
ass.
Boylston
St.
1 step

17. 17
Boston
Marathon
bombings
Boston
Marathon
Watertown,
Mass.
Boston, M
ass.
Boylston
St.
1.5-step

18. Communities
Perpetrators
MIT PD
Watertown, Mass.
Shelter in place
Holy Cross
Pressure cooker

19. Burst detection
19
Rolling 30 day average
2x
SE

20. Largest bursts
1. Ground stop (329)
2. Boylston Street (268)
3. Google Person Finder (237)
4. Patriots’ Day (201)
5. Copley Square (171)
6. Controlled explosion (168)
7. Lenox Hotel (116)
8. Pressure cooker (83)
9. MA EMA (83)
10. BP SOU (78)
20

21. 21
April 15

22. April 16
Pressure cooker

23. April 17
Holy Cross

24. April 18
MIT PD
Watertown, Mass.
Shelter in place

25. April 19

26. April 20

27. April 21

28. 28
COAUTHORSHIP NETWORK
28

29. Types of networks
• Markup
• Hyperlinks: i has a link to j
• Revisions
• Coauthorship: i shares an editor with j
• Pageview activity
• Correlation: i’s pageviews correlated with j

30. Coauthorship activity 4/15 – 5/1
30

31. 31
CORRELATION NETWORKS

32. Types of networks
• Markup
• Hyperlinks: i has a link to j
• Revisions
• Coauthorship: i shares an editor with j
• Pageview activity
• Correlation: i’s pageviews correlated with j

33. Temporal correlation networks

34. 34
Duffel bag
New York
Times
MGH
Activity correlation network

36. 36
DISCUSSION

37. Theoretical framework
• Information seeking and sense-making
• Fine-grained traces of large-scale behavior in a
complex information space
• Mass convergence and crisis informatics
• Nearly real-time behavior captures bursts of activity
related to current events
• Networks of knowledge and collaboration
• Information seeking in knowledge network drives
creation of new knowledge and relationships

38. Future directions
• Track diffusion of bursts across larger hyperlink
network
• Are distant bursty events responsible for substantial
fraction of editing activity?
• Synchronized and anomalous bursts of activity
as narrative elements
• Czech Republic vs. Chechnya
• Classifying events and mobilizing resources

39. Future directions
• Textual features predict bursts?
• Edit distance, number of mentions, position on
page, etc. convey relatedness of content
• Multilevel & longitudinal statistical model of tie
formation
• Dyadic covariates: Pageview correlation 
coauthorship ties  hyperlinks

40. 40
THANK YOU!
Brian Keegan
b.keegan@neu.edu
www.brianckeegan.com
@bkeegan
40