1 / 8

Analysis of Social Information Networks

Analysis of Social Information Networks. Thursday January 20 th , Introductory Lecture. Motivation. 2010 was a “social year” Time Person of the year The “social network” makes $200m box office Facebook is 3 rd largest “country” . What’s behind the scene? .

sheng
Download Presentation

Analysis of Social Information Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Analysis of Social Information Networks Thursday January 20th, Introductory Lecture

  2. Motivation 2010 was a “social year” Time Person of the year The “social network” makes $200m box office Facebook is 3rd largest “country” What’s behind the scene? What does it mean for computer scientists? What about 2011, 2016, 2021?

  3. A key principle • What primarily matters is your social environment! • For Business: how to best advertise a product? • For Media: how to extract sound and relevant information? • For Engineers-CS: how to best design an application? • For Science at large: how to understand tipping points? … 4 (classical) questions, being reinvented today

  4. Social Information Networks • Large set of personal information about users • History of Browsing, Purchasing, Rating • Sociological profile (age, gender, location, income) • Community of interests • Large set of relational information about users • Connections (friendship, collaboration, schoolmate) • Contacts (email IM phone calls etc., meeting)

  5. Computer scientists needed! • In the industry: • Users’s data are company’s key differentiating factor • You (not me) are the social media generation! • In the academia: • CS handles “complexity” with depth and elegance. • A growing trend (ex: Columbia, Cornell, U. Penn)

  6. Before starting the trip • The topic is broad: “CS-theory, Networking, Sociology, Physics” • This is why the course focuses on algorithmic prop. • The topic seems (at times) immature: “What is a good model? a cause? a correlation?” • Algorithmic research problems have an impact • Involves some mathematical notions: • Goal: self-contained(do ask for more background)

  7. Organization • 8 first lectures: “fundamentals” • Weekly review homework (contains 2/3 of midterm) • Your participation: scribing • 6 last lectures: “advanced topics” • Bird’s eye view of social media + new trends • Your participation: paper presentation & discussions • Projects: topic review or research case study • Office hours: Wednesday 2-3:30pm, CEPSR 610

  8. A taste of what you’ll see • Power-law: How popular items build up? • Epidemics: How gossip (and virus) propagates? • Influence: What can promote or block innovation? • Hidden structures: • Ranking: How to select the most important items? • Similarity: How to exploit others’ tastes ? • Division: How to cut networks • Overview of latest data and empirical dynamics. • A session on mobile social services?

More Related