1. time for events
telling the world’s stories from social media
Mor Naaman
Rutgers SC&I & Mahaya, Inc.
@informor

4. enter: social media

5. (JCDL 2007)

6. (JCDL 2007)

7. (SIGIR 2007)
yes.

8. organize the world’s memories

9. people, together

10. BYOBW

11. outside lands festival

15. organize the world’s memories

16. detect
identify
organize
objectives

17. objectives
detect
ICWSM 2011a
JASIST 2011
WebDB 2009
SIGIR 2007

18. objectives
identify
WSDM 2012
ICWSM 2011b
WSDM 2010

19. objectives
organize
ICMR 2012
CHI 2012
CSCW 2012
MTAP 2012
VAST 2010
WWW 2009

20. today
organize
identify
detect
Vox!
multi-site
Multiplayer

21. overview E Multi-site content
Vox Civitas
Multiplayer

22. E
goal
effectively retrieve social media content
for known events from multiple services
[with Hila Becker, Luis Gravano]

23. E

24. E
challenges
event descriptor not well-formed
brief textual descriptors
noise
formats/conventions/metadata differ

25. E
approach
two-step query formulation
precision-based
recall-based
validate queries based on known/
extracted event model

26. E
E
step 1
term extraction from event descriptors
generates “high precision” queries
e. g. “andrew bird, opening gala,
celebrate brooklyn, prospect park”

27. E
E
step 2
use “high precision” corpus to generate
more general queries to improve recall
e. g. “andrew bird concert”, “state farm
insurance”

28. E
E
recall-oriented queries
Benefits:
- Works cross-site
- Works with short content
Challenges:
- Introduces noise
- Potentially large set of queries

29. E
E
post-filtering
use known event model (topics, time,
location)
use queries with a result set that
matches known model

30. E
E
for example...
120"
100"
80"
60"
40"
20"
0"
6/7/11" 6/8/11" 6/9/11" 6/10/11" 6/11/11" 6/12/11" 6/13/11"
[andrew"bird"concert]" [state"farm"insurance]"

31. E
evaluation
1.1"
query generation4"
1" 4"
0.9"
0.8" 5" 5" Precision"
0.7"
relevance of36"retrieved documents
NDCG%
0.6"
39" 34" 34"
Twi7er8MS"
0.5"
0.4"
0.3" YouTube8MS"
7"
0.2" 9" 8" 8"
0.1"
0"
0" 5" 10" 15" 20" 25"
Number%of%Documents%k%

32. E
takeaways
can aggregate content fragmented
across platforms
improve recall, not rely on site-specific
features

33. overview E Multi-site content
(WSDM 2012)
Vox Civitas
Multiplayer

35. research questions
can Twitter content around broadcast
news events inform journalistic inquiry?
what insights and analyses can we
enable through visual analytic tools?
[with postdoctoral fellow Nick Diakopoulos]

36. supporting analysis
direct attention to relevant information
automatic content analysis for filtering
– relevance
– uniqueness / novelty
– sentiment
– keyword extraction

38. how to evaluate?
directly evaluate the output of the
algorithms (quantitative)
deep, extensive evaluation of users’
interaction with the system (qualitative)
read more: Olsen (UIST ’07)
Naaman (MTAP ’12)

39. Vox evaluation goals
• How effective for generating story ideas?
• What kind of insights/analysis are
supported?
• Shortcomings and how features are
used?

40. takeaways
can extract reliable event structure from
social media

41. overview E Multi-site content
Vox Civitas
(VAST 2010)
Multiplayer

42. what the hell?
[with: Lyndon Kennedy, Dan Ellis, Kai Su]

47. supporting analysis
extract the signal from people’s
attention:
find overlapping moments
compute and rank scenes
extract scene descriptors

48. audio fingerprinting
Wang et al. (ISMIR ’03)

49. two clips, aligned
0:18
3:32
0:00
0:00
2:32

50. a story of n clips
time

51. from clips to scenes
Higher Ground
Encore
time Happy Birthday,
Birthday

53. evaluation
quantitative: evaluated matching, scene
extraction…
qualitative: evaluated deployment
scenario/task

54. takeaways
can create an event presentation that
gets better them more content is added

55. overview E Multi-site content
Vox Civitas
Multiplayer
(NM&S 2012, ICMR 2012,
MTAP 2012, WWW 2009)

57. towards better models of
large-scale human attention

58. printing press

59. è knowledge archive

60. digital documents

61. èdigital archive

62. the web

63. ènetworked archive

64. social media

65. èexperience archive

66. new methods?

67. search by subject code?

68. explore.
new information seeking tasks (and
models)
new applications for social media
content

69. explore.
beyond real-time
personal and social

70. questions?
mor@rutgers.edu
@informor
http://mornaaman.com

71. thanks
Luis Gravano
Hila Becker
Nick Diakopoulos
Kai Su
Dan Ellis
Munmun de Choudhury
Tarikh Korula
…