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Discovering Leaders from Community Actions

This paper explores the discovery of leaders and tribe leaders from social networks and action logs. The authors propose a framework based on frequent pattern mining to identify leaders in social networks. The objective is to target these leaders for the adoption of new products, potentially benefiting companies through targeted advertising. The methodology includes parameters such as maximum propagation time threshold and actions performed by users. Experiments demonstrate the effectiveness of the framework in identifying leaders and tribe leaders. The paper concludes by highlighting the potential applications in viral marketing.

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Discovering Leaders from Community Actions

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  1. Discovering Leaders from Community Actions Presenter : Wu, Jia-Hao Authors : Amit Goyal , Francesco Bonchi , Laks V. S. Lakshmanan 國立雲林科技大學National Yunlin University of Science and Technology CIKM (2009)

  2. Outline • Motivation • Objective • Methodology • Experiments • Conclusion • Personal Comments

  3. Motivation • We have some interactions with you and me in the internet actives that can be a social networks. • like rating songs as in Yahoo! Music or Yahoo! Movies or users burying gadgets such as cameras , handhelds… I want to buy. Write Buy I want to buy.

  4. Write Actions log Buy Objective • The authors want to find the leaders and tribe leaders from the social networks and action log. Leader Actions log Buy Tribe Leader

  5. Propagation of action a Action log Social networks Propagation of action b Objective (Cont.) • The authors want to find the leaders and tribe leaders from the social networks and action log.

  6. Write Objective (Cont.) • If we know that there are a small number of leaders who set the trend for various actions. • Targeting them for adoption of new products could be profitable to the companies (Targeted advertising).

  7. Leader Propagation of action a Tribe Leader Propagation of action b Methodology • Parameters • ：maximum propagation time threshold • ：number of the node in action α • ：a number of actions by the user u

  8. Methodology (Cont.) • Leadership confidence • Genuineness score of v Constraint 1. Constraint 2.

  9. R S T W V Methodology (Cont.) – Computing Influence Matrix

  10. R S T W V Methodology (Cont.) – Propagate OR P

  11. R S T W V Methodology (Cont.) – Update P OR Q

  12. Methodology (Cont.) - Computing • Leaders • Genuineness Leaders • Tribe Leader

  13. Experiments

  14. Experiments (Cont.)

  15. 206280 198671 75293 68241 130514 22380 130514 20045 170467 Experiments (Cont.)

  16. Conclusion • The authors purpose notions of leaders and tribe leaders together with possible additional properties such as confidence and genuineness. • Use the two key operations – update and propagate to search the changes of social network graph. • The result is the first proposal of a framework based on frequent pattern mining for discovering leaders in social networks.

  17. Comments • Advantage • An interest research about the community actions. • Drawback • There have some parameters in algorithms and paper. • Application • Viral Marketing.

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