Sie sind hier

Online Crowd Behavior and Production

The course discusses theories, methods and algorithms used to understand and shape online crowd behavior and the production of digital goods and services by crowds. Examples come from collaborative authoring systems, social media, online social networks and health applications. The goal of this course is to enable students to competently analyze and understand crowd behavior and –production in online environments.

Learning Goals

Students taking this course will be able to:

  • Understand online crowd behavior and –production research and the literature it generates

  • Analyze online crowd behavior and –production in specific application domains, with a focus on social media and health related applications.

  • Discuss selected instruments and methods to shape online crowd behavior and –production

  • Know how to evaluate crowd-based production systems

  • Understand relationships between online crowd behavior and the artifacts it generates

  • Appreciate the social-computational complexity of online crowd behavior and –production

Preliminary Week by Week Outline

Week 1: Motivation and introduction

A general introduction and motivation of the topics of this seminar will take place.

In Week 1, students will pick the topics (from subseqent weeks) that they will present, discuss and research on during the course of the seminar.

 

BREAK: A couple of weeks break for students to work on their topics. 

 

Week 2: Encouraging contributions from online crowds

We will discuss how contributions from online crowds can be encouraged and shaped.

Week 3: Online crowd formation and consensus engineering

In this week, we will discuss the ways in which crowds form and how consensus emerges.

Week 4: Models of influence

In this week, we will discuss different models of influence in online crowds, and the reflection problem.

  • David Easley and Jon Kleinberg, Chapter 16. Information Cascades, In Networks, Crowds, and Markets: Reasoning About a Highly Connected World, Cambridge University Press (2010)

http://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch16...

  • David Easley and Jon Kleinberg, Chapter 19. Cascading Behavior in Networks, In Networks, Crowds, and Markets: Reasoning About a Highly Connected World, Cambridge University Press (2010)

http://www.cs.cornell.edu/home/kleinber/networks-book/networks-book-ch19...

  • Charles F Manski, Identification of Endogenous Social Effects: The Reflection Problem, The Review of Economic Studies, Volume: 60, Issue: 3, (1993) Pages: 531-542

http://fisher.osu.edu/~schroeder_9/AMIS900/Manski1993.pdf

Week 5: Conflict and coordination

In this week, we will discuss mechanisms of conflict and coordination in collaborative authoring systems such as wikis.

Week 6: Identifying expertise & experts

The identification of experts and expertise in online crowds will be discussed in this week.

Week 7: Voting mechanisms and manipulation

In this week we will discuss mechanisms of manipulation of crowds, and how to tackle them.

Week 8: Crowdsourcing and microwork

In this week, we will discuss microworking platforms such as Mechanical Turk.

Week 9:Analyzing epidemics in crowd-generated data

In this week, we will discuss epidemic models and how crowd-generated data can be utilized for identifying epidemics.

Week 10: Crowd Production of Medical Knowledge

In this week, we will discuss an ongoing effort to crowdsource a large medical taxonomy.

Deliverables

  • A presentation and leading a corresponding discussion on a selected topic (during the seminar)

  • A paper, 6 pages ACM Style (at the end of the seminar)

Required Texts