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Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study

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Chenxi Yang, Yang Chen, Qingyuan Gong, Xinlei He, Yu Xiao, Yuhuan Huang, Xiaoming Fu. Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study. Big Data Mining and Analytics, 2018, 1(4):284-296.

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Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study

  1. 1. Nov/14/2018 Understanding the Behavioral Differences Between American and German Users: A Data-Driven Study Chenxi Yang1, Yang Chen1, Qingyuan Gong1, Xinlei He1, Yu Xiao2, Yuhuan Huang3, Xiaoming Fu4 Fudan Univ.1, Aalto Univ.2, Guangdong Univ. of Foreign Studies3, Univ. of Gö̈ttingen4 Big Data Mining and Analytics, 2018, 1(4):284-296.
  2. 2. Traditional Cultural Analysis Offline Questionnaires Video Documentation Paper Documentation
  3. 3. Online Social Networks (OSNs) ✤ Billions of users worldwide ✤ Situation-aware interactive information
  4. 4. Related Work & Problems ✤ Facebook Survey [Krasnova et al., HICSS’10]: Explore the differences to self-disclosure between American and German Not large enough to form a cultural impact Lack of data comprehensiveness Only the answers to the questions or users’ posts Lack of movement pattern and points-of-interest (POIs)
  5. 5. Solution: LBSNs ✤ Location-Based Social Networks - Location-centric activities - Social interactions - Viable data source Case Study: American & German Users in Yelp
  6. 6. Contributions ✤ Provide a comprehensive demographic analysis of American and German users’ behavior - Friends’ distribution - Daily schedule - Collectivism & individualism - A classification model detecting cultural background ✤ Verify the feasibility of applying big data analysis in the context of cultural behavior
  7. 7. Dataset Introduction ✤ Yelp The world’s largest online “urban guide” and business review sites - 4,700,000 reviews - 156,000 businesses - 1,100,000 users ✤ Yelp Open Dataset
  8. 8. Data Analysis: Social Graph ✤ More friends on Yelp: American ✤ Higher proportion of influential users: American Nation Avg. CC Var. CC Avg. Degree Var. Degree Avg. PageRank Var. PageRank USA 6.045 0.252 2.298 1.845 0.087 0.438 Germany 4.688 0.191 0.965 2.842 0.017 0.288
  9. 9. Data Analysis: Social Graph ✤ German users’ friends are gathered in fewer cities ✤ The location distribution of American users’ friends is slightly wider Location distributions of friends of American and German users
  10. 10. Data Analysis: Writing Styles ✤ More affective: American ✤ Collectivism: German Individualism: American Occurrence Frequency of Different Categories of Words in Reviews Dimension Values of American and German Users Nation Affect Anger Tenta Certain Swear Friends USA 6.045 0.252 2.298 1.845 0.087 0.438 Germany 4.688 0.191 0.965 2.842 0.017 0.288 Nation Category I We USA Beauty & Spas 7.02 0.53 Health Medical 6.85 0.61 Home Services 4.89 1.61 Nightlife 3.72 1.79 Restaurant 4.08 1.49 Shopping 5.47 0.88 Avg. 5.34 1.15 Germany Beauty & Spas 4.17 0.27 Health Medical 3.58 0.31 Home Services 2.16 1.05 Nightlife 1.73 1.29 Restaurant 1.78 1.34 Shopping 3.04 0.46 Avg. 2.74 0.79
  11. 11. Data Analysis: Business Categories Category Pattern ✤ “Food”, “Nightlife” and “Shopping”: Similar ✤ “Restaurants” and “Public Services”: German
  12. 12. Data Analysis: Rating ✤ Most users: Good rating ✤ American: Wilder rating German: Milder rating Distribution of the Number of Stars
  13. 13. Data Analysis: Check-in Patterns ✤ Differences of noon peak and night peak ✤ Mealtime & Bedtime Here-now Count Patterns
  14. 14. Cultural Background Classification ✤ Category: 7 features ✤ Social Graph: 4 features ✤ Writing Style: 10 features ✤ Visit & Rating: 4 features Overview of the Classification Model
  15. 15. Cultural Background Classification ✤ The writing style-related feature set: Pivotal ✤ The social graph-related feature set: Significant Rank X2 Feature Category 1 969.876 Pronoun Writing Style 2 650.939 Preps Writing Style 3 366.716 Tentat Writing Style 4 268.432 Certain Writing Style 5 199.665 CC Social Graph 6 99.615 Friends Distribution Social Graph 7 85.471 PageRank Social Graph 8 73.282 Swear Writing Style 9 60.701 Beauty & Spas Business Category Precision Recall F1-score AUC Writing Style 0.879 0.878 0.878 0.937 Social Graph 0.741 0.741 0.741 0.823 Business 0.623 0.612 0.617 0.660 Visit & Rating 0.602 0.603 0.601 0.619
  16. 16. Conclusions ✤ Use the behavioral information of massive users to explore the differences between American and German users from a cultural perspective ✤ Validate our analysis results with a cultural background classification model and gain a better understanding of the importance of various feature sets in forming a human behavior pattern
  17. 17. Future Work We aim to build an overall online behavior pattern set of cultural consequences applied to people with fine- grained cultural backgrounds.

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