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Exploring Social Computing: Theory, Algorithms, and Online Networks

Dive into the foundations of social computing, approximation algorithms design, and research frontiers to understand social networks and their computational analysis. Learn about online social networks and community structures. This course introduces theoretical foundations and essential results in social computing. Gain insights into social influence, rumor blocking, and power laws. Discover the significance of social networks in representing social relations. Explore practical applications and optimize social influence.

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Exploring Social Computing: Theory, Algorithms, and Online Networks

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  1. cs6301 Introduction to Social Computing • Ding-Zhu Du • University of Texas at Dallas lidong.wu@utdallas.edu

  2. Abstract • Computer network has been used to represent and to build up social relations, called social networks which forms a basis to study social science. Such study is a new research area in computer science, called social computing. This course will introduce theoretical foundation for social computing and fundamental results in theory of social computing.

  3. Goal • Let students learn techniques in design and analysis of approximation algorithms, especially those appearing in study of social computing. • Lead students to frontier of research in social computing.

  4. Computational Social Networks --computational data networks • Weili Wu Ding-Zhu Du • University of Texas at Dallas lidong.wu@utdallas.edu

  5. Reference books

  6. Theory of Social Computing --computational social networks • Weili Wu Ding-Zhu Du • University of Texas at Dallas lidong.wu@utdallas.edu

  7. Abstract • Computer network has been used to represent and to build up social relations, called social networks which forms a basis to study social science. Such study is a new research area in computer science, called social computing. This book will introduce theoretical foundation for social computing and show you fundamental results in theory of social computing.

  8. Not “Prerequisites”

  9. Upcoming Springer Book: Optimal Social Influence • Wen Xu, Weili Wu • University of Texas at Dallas lidong.wu@utdallas.edu

  10. Lecture 1-1 What is a Social Network? • Ding-Zhu Du • University of Texas at Dallas lidong.wu@utdallas.edu

  11. Outline • Social Network • Online Social Networks • Community Structure • Rumor Blocking • Power Law

  12. What is a Network? Web definition: A network consists of two or more nodes that are linked in order to share resources.

  13. What is Social Network? Wikipedia Definition: Social Structure • Nodes:Social actors (individuals or organizations) • Links:Social relations

  14. Example 1: Friendship Network • Nodes: all persons in the world • A link exists between two persons if they know each other.

  15. Property of Friendship • Six Degrees of Separation • Milgram (1967) • The experiment: • Random people from Nebraska were to send a letter (via intermediaries) to a stock broker in Boston. • Could only send to someone with whom they know. • Six links were needed. Stanley Milgram (1933-1984)

  16. Chinese Observation • 八竿子打不着 • 形容二者之间关系疏远或毫无关联。“竿”也作“杆”。

  17. Lidong Wu Friend Friend Roommate Family Friend Supervise Friend Family Friend

  18. “The small world network is a type of mathematical graph in which most nodes are not neighbors of one another, but most nodes can be reached from every other by a small number of hops or steps.”

  19. Example 2:Coauthorship Network • Nodes: all publication authors • A link exists between two authors if they are coauthors in a publication.

  20. Coauthorship Network is a Small World Network Distribution in Dec.2010 Erdös number  0  ---      1 personErdös number  1  ---    504 peopleErdös number  2  ---   6593 peopleErdös number  3  ---  33605 peopleErdös number  4  ---  83642 peopleErdös number  5  ---  87760 peopleErdös number  6  ---  40014 peopleErdös number  7  ---  11591 peopleErdös number  8  ---   3146 peopleErdös number  9  ---    819 peopleErdös number 10  ---    244 peopleErdös number 11  ---     68 peopleErdös number 12  ---     23 peopleErdös number 13  ---      5 people * Two persons are linked if they are coauthors of an article. • Erdős number: is the collaboration distance with mathematician Paul Erdős. What is your Erdős number?

  21. My Erdős number is 2.

  22. Example 3:Flight Map Is a Small World Network • Nodes: all cities with an airport. • A link exists between two cities if there exists a direct flight between them.

  23. Search Cheap Ticket • Find a cheap ticket between two given cities. • It is a shortest path problem in a social network. • Need to add connection information to network. There are about 28,537 commercial flights in the sky in the U.S.on any given day.

  24. Network Construction AA123 AA456 Chicago Dallas AA789

  25. Network Construction 8am 8am 9am 9am 1pm 1pm 3pm 3pm Dallas

  26. Network construction 8am 8am 9am 9am 1pm 1pm 3pm 3pm Dallas

  27. Outline • Social Network • Online Social Networks • Community Structure • Rumor Blocking • Power Law

  28. Social Network is online in Internet • Facebook: friendship • linkedIn: friendship • ResearchGate: coauthorship

  29. Online Social Networks (OSN) • Social influence occurs when one's emotions, opinions, or behaviors are affected by others. • Although social influence is possible in the workplace, universities, communities, it is most popularonline.

  30. Internet provides a platform to record and to develop social networks

  31. What Are OSN Used For?

  32. Usage Example Political Election for Mayor of London (2012) Candidates (left to right) : Ken Livingstone, Boris Johnson and Brian Paddick. http://www.telegraph.co.uk/technology/news/9239077/Twitter-data-predicts-Boris-Johnson-victory.html

  33. Prediction of Boris Johnson Victory

  34. How to Predict? • Analysis posts on Facebook and Twitter: “Sentiment Analysis” . • Find 7% more positive sentiment towards Mr. Johnson than Mr. Livingstone. • Predict 54% of the vote for Mr. Johnson. • Google Insights, tracking web trends, • Almost five times more searches for “Boris Johnson” than for “Ken Livingstone” via google.co.uk. • Of the total number of web searches for both candidates, 60% were for “Boris Johnson”.

  35. Outline • Social Network • Online Social Networks • Community Structure • Rumor Blocking • Power Law

  36. Question 1? Does Six Degrees of Separation imply six degrees of influence?

  37. Three Degrees of Influencein friendship network

  38. Three Degrees of Influence In Book Connected by Nicholas A. Christakis and James H. Fowler.

  39. Three Three Degrees of Influence • The influence of actions ripples through networks 3 hops (to and from your friends’ friends’ friends).

  40. I am happy!

  41. Question 2? How to explain Six Degrees of Separation and Three Degrees of Influence?

  42. Community • People in a same community share common interests in • - clothes, music, beliefs, • movies, food, etc. • Influence each other strongly.

  43. Community Structure Community with overlap Community without overlap * same color, same community

  44. Community Structure In the same community, • two nodes can reach each other in three steps. • A few of tied key persons: C, D • Member A reaches Member B via A-C-D-B

  45. Community Structure For different communities, • Two nodes may have distance more than three.

  46. Community Structure For two overlapping communities, • Two nodes can reach each other by at most six steps. A B C

  47. Outline • Social Network • Online Social Networks • Community Structure • Rumor Blocking • Power Law

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