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Panpan Xu 1, Yingcai Wu 2, Enxun Wei 2, Tai-Quan Peng 3, Shixia Liu 2, Jonathan J.H. Zhu 4, Huamin Qu 1 … … … Visual Analysis of Topic Competition 1 Hong.

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Presentation on theme: "Panpan Xu 1, Yingcai Wu 2, Enxun Wei 2, Tai-Quan Peng 3, Shixia Liu 2, Jonathan J.H. Zhu 4, Huamin Qu 1 … … … Visual Analysis of Topic Competition 1 Hong."— Presentation transcript:

1 Panpan Xu 1, Yingcai Wu 2, Enxun Wei 2, Tai-Quan Peng 3, Shixia Liu 2, Jonathan J.H. Zhu 4, Huamin Qu 1 … … … Visual Analysis of Topic Competition 1 Hong Kong University of Science and Technology 2 Microsoft Research Asia 3 Nanyang Technological University 4 City University of Hong Kong on Social Media VAST 13 1

2 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Diffusion of multiple topics The Interaction: Do people get distracted away from some topics when something more “eye- catching” is happening? The Influence: How do the opinion leaders (influential users) affect the interaction by recruiting the public attention for some topics? On Social Media: 2 Google Ripples

3 Whisper [N. Cao et al. 12] 3 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Google Ripples [F. Viégas et al. 11]

4 Agenda-setting The ability of the news media (e.g. TV and newspaper) to influence the salience of topics on the public agenda. Topic competition Two-step information flow The addition of any new topic onto the public agenda comes at the cost of other topic(s). INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY [M. E. McCombs and D. L. Shaw 72] [J. Zhu 92] [S. Wu et.al 11] The information reaches the masses via intermediaries. 4

5 Agenda-setting The ability of the news media (e.g. TV and newspaper) to influence the salience of topics on the public agenda. Topic competition Two-step information flow The addition of any new topic onto the public agenda comes at the cost of other topic(s). INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY [M. E. McCombs and D. L. Shaw 72] [J. Zhu 92] [S. Wu et.al 11] The information reaches the masses via intermediaries. 5

6 Agenda-setting The ability of the news media (e.g. TV and newspaper) to influence the salience of topics on the public agenda. Topic competition Two-step information flow The addition of any new topic onto the public agenda comes at the cost of other topic(s). INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY [M. E. McCombs and D. L. Shaw 72] [J. Zhu 92] [S. Wu et al. 11] The information reaches the masses via intermediaries (opinion leaders). 6

7 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Combine quantitative modeling and interactive visualization Healthcare #debate #china Extract time varying measurements on topic competitiveness each opinion leader group’s influence on each topic topic transition trend of each opinion leader group Visualize the dynamic relation between topics and opinion leader groups textual contents of the posts 7

8 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Collection of Tweets Text Search Time Series: Stream of tweets Topic User group Topic Competition Modeling Topic Transition Analysis Combine quantitative modeling and interactive visualization Timeline Visualization Raw Tweets List Word Cloud 8

9 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Collection of Tweets Text Search Time Series: Stream of tweets Topic User group Topic Competition Modeling Topic Transition Analysis Combine quantitative modeling and interactive visualization Timeline Visualization Raw Tweets List Word Cloud 9

10 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Collection of Tweets Text Search Time Series: Stream of tweets Topic User group Topic Competition Modeling Topic Transition Analysis Combine quantitative modeling and interactive visualization Timeline Visualization Raw Tweets List Word Cloud Time-varying topic competitiveness Each opinion leader group’s influence Topic transition trend 10

11 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Collection of Tweets Text Search Time Series: Stream of tweets Topic User group Topic Competition Modeling Topic Transition Analysis Combine quantitative modeling and interactive visualization Timeline Visualization Raw Tweets List Word Cloud 11

12 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY [J. Zhu 92] distraction effect Topic Competition Model for traditional media : recruiting effect 12

13 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY recruiting effect [J. Zhu 92] Topic Competition Model for traditional media : 13

14 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY [J. Zhu 92] distraction effect Topic Competition Model for traditional media : 14

15 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY The Extended Topic Competition Model: Two step information flow Heterogeneous influence (news media, grassroots) 15

16 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY The Extended Topic Competition Model: Two step information flow Heterogeneous influence (news media, grassroots) distraction effect recruiting effect 16

17 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY … … … … Topic Transition Estimation Transition matrix 17 T T-1

18 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Collection of Tweets Text Search Time Series: volume of tweets Topic User group Topic Competition Modeling Topic Transition Analysis Timeline Visualization Raw Tweets List Word Cloud Output of Analysis and Modeling Step: Time varying competitiveness of each topic Time varying opinion leader groups’ influence on each topic The topic transition trend of the opinion leader groups between adjacent time stamps. 18

19 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Topic competiveness Timeline view 19

20 Media Political Figures Grassroots Topic competiveness + Recruitment effect of different opinion leaders + Topic transition trend Timeline view INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Word Cloud 20

21 21 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Word cloud filterable by: Topic Time interval Opinion leader group Sparkline: Time varying saliency of a word

22 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Dataset: 2012 Presidential Election; 89, 174, 308 tweets; May 01 – Nov 10 Six general topics : welfare/society, defense/international issues, economy, election (general), election (horse race), law/social relations * Three opinion leader groups: media, political figures, and grassroots * *identified collaboratively with media researchers 22

23 23 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY Election (general)

24 24 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY

25 25 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY

26 26 INTRO / SYSTEM / MODEL / DESIGN / CASE STUDY

27 SUMMARY / LIMITATIONS & FUTURE WORK Collection of Tweets Text Search Time Series: volume of tweets Topic User group Topic Competition Modeling Topic Transition Analysis Timeline Visualization Raw Tweets List Word Cloud Visual analysis framework: Model the topic competition on social media, the influence of opinion leader groups, and the topic transition trends. Visualize the results of the models and allow for further exploration to form explanations. 27

28 SUMMARY / LIMITATIONS & FUTURE WORK Manual process to collect keywords and categorize opinion leaders more efficient ways? Time series modeling + the structural factors of social network ? Competition & cooperation other modes of interaction among topics? 28

29 29 Thank You for Attention !

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