Understanding the Dynamics of Knowledge

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Erick Grant
5 years ago
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1 Visual Analysis of Conflicting Opinions Chaomei Chen, Drexel University USA Fidelia Ibekwe-SanJuan, Université de Lyon, France Eric SanJuan, Université d Avignon Avignon, France Chris Weaver, Penn State University, USA

2 Understanding the Dynamics of Knowledge 1. What is the hottest topic at time T0? 2. What are the hot topics between time Ta and Tb? (A Timeline - Temporal) 3. What are the major turning points between time Ta and Tb? (Turning points - Structural) 4. How did knowledge associated with these turning points spread? (Diffusion - Spatial) 5. How can we differentiate various perspectives and views based on a large volume of inputs? (Sense- Making - Semantics) 2

3 A quick CiteSpace demo Topic: Terrorism Time span: Q1: Current hot topic? Q2: Previous hot topic? Q3: Turning point? Q4: Transition path? 1. What is the most active topic in the area of TERRORISM RESEARCH? 2. What was the previously predominant topic? 3. What EVENT/WORK led to the shift of focus? 4. What is such a transition path made of? before after 3

4 CiteSpace WebStart 4

5 Q2: Previous hot topic? Q3: Turning point? Q4: Transition path? Q1: Current hot topic? 5

6 Bird flu spread in Thailand Computer model map of new cases (red) and where the epidemic has finished (green) days after an uncontrolled outbreak 6

7 Geospatial patterns of terrorist events 7

8 Geospatial patterns of relevant research 8

9 The Impact of a Pivotal Point Glea,, S. et al. (2002) How does the citations to this paper spread geographically? 9

10 2002 USA 10

11 2003 USA 11

12 2004 USA 12

13 2005 USA 13

14 2006 USA 14

15 Citers to Galea et al. (2002) 15

16 Differentiating Conflicting Views 1,738 positive reviews (=4, 5) 918 negative reviews (=1, 2) 16

17 The Role of Rare Terms To differentiate conflicting opinions, it is necessary to identify unique perspectives represented by low frequency terms Term variations TermWatch Log likelihood tests Decision Trees 17

18 amazon.com web services customer reviews Data Collection TermWatch LT chunker extract terms identify term variations cluster terms Predictive Text Analysis POS tagging term extraction term selection predictive models Text Analysis term variation graph decision trees coordinated views Visual Inspection 18

19 Term Variations modifier head word Operations Term Term Variation Syntactic (adding a modifier) secret society ancient secret society Syntactic ti clever plot clever plot twist t (adding a head word) Syntactic renowned Harvard professor famous Harvard professor (changing a modifier) Syntactic (changing a head word) Semantic (synonymous) secret book ingenious plot secret agenda clever plot 19

20 Term Variations Head substitution age-old religious secret age-old religious mystery ExpansionE i action thriller perfect suspense action thriller amusing speculation amusing speculation collection roller coaster electrifying roller coaster ride Association mind-binding puzzle 5-star entertainment 20

21 Positive Reviews Negative Reviews 21

22 22

23 Drilling down the really good book cluster 23

24 When good thriller writing is used negatively 24

25 25

26 Document Frequency vs. Log Likelihood (p=0 0.5) 29,837 Features 26

27 The Power of Rare Terms green (< 0.001), 001) blue (p=0.001), 001) red (=0.01), 01) pink(=0.5) 27

28 Feature Selection: Doc Freq vs. Log Likelihood Classification accuracy based on 10-fold cross-validation: C4.5 << NaiveBayes << SVM 28

29 The Da Vinci Code (Amazon Sales Rank: 7) 3,068 Customer Reviews 29

30 The Tipping Point (Amazon Sales Rank: 12) 596 Customer Reviews 30

31 Document Frequency vs. Log Likelihood 31

32 686 Customer Reviews Video ipod (accuracy 91.49%) Amazon.com Sales Rank: #12 in Electronics 32

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34 34

Emergent themes over time on terrorism (2001-2005)

Concrete Structure Case Studies Biological Warfare

35 Emergent themes over time on terrorism ( ) Support Vector Classifier Biological Weapon Health Care America s War Military Strategy Many voice Chemical Weapon Emergency Preparedness Concrete Structure Case Studies Biological Warfare Risk Assessment Survey Assessment Global Justice

36 Biological Weapon Health Care America s War Military Strategy Many voice Chemical Weapon Emergency Preparedness Concrete Structure Case Studies Biological Warfare Risk Assessment Survey Assessment Global Justice 36

37 Emergent themes over time on terrorism ( ) A decision tree derived from 3,944 abstracts Old New Old Old NewNew Old New New Old Old New 37

38 Summary Visual Analysis of Conflicting Views Feature selection and handling low-frequency but critical features and interrelationship Term variation patterns Statistical tests of associations Facilitate sense making tasks What information is the most effective to understand different opinions? How could emergent thematic patterns be visualized? Future Work Integration with more interactivity Comprehensive evaluations of alternative approaches Investigations of the applicability in a wider range of visual analytic tasks 38

39 Acknowledgements National Visualization and Analytics Center (NVAC) Northeast Visualization and Analytics Center (NEVAC) NSF IIS Award # SEI: Coordinated Visualization and Analysis of Sky Survey Data and Astronomical Literature 39

SOCIAL DESIGN U X W E E K

THE PSYCHOLOGY OF SOCIAL DESIGN U X W E E K 2 0 0 7 JOSHUA PORTER - BOKARDO DESIGN Social Psychologist KURT LEWIN founder of social psychology LEWIN S EQUATION B=ƒ(P,E) Behavior is a function of the Person