Special Course on Web Science

Course Materials

• Slides and recordings
  

Motivation

The rapidly growing popularity of online communication platforms and social networks (Facebook, Twitter, Bebo, WordPress, and many others) results in a new, purely virtual societal form with its own dynamics, evolution patterns, social opinions and trends. Nowadays, this online social phenomenon is known as "eSociety".

The way of thinking about publishing and using data on the Web is also rapidly changing.  The idea of the new Linked Open Data (LOD) paradigm is the data-centric linking between facts and objects across different repositories, social platforms, and "Deep Web" information sources (expert databases, business data, libraries, patent repositories, etc.).

The key idea of Web Science: interdisciplinary, multi-aspect analysis of Social Web and LOD. Web Science adopts methods from psychology, social sciences, social network analysis, multi-modal content analysis, as well as Web retrieval. The key objective is to improve information organization and information access in the modern Web society.

Target group: The special course addresses master and diploma students in Computer Science, Information Management, and Computer Visualistics that aim to improve their expertise in Social Web, Linked Open Data, and state-of-the-art Web Retrieval. Recommended prerequisites are courses in "Information Retrieval", "Web Mining" as well as "Databases".

The course will be offered in the 2+0 SWS mode (3 ECTS), i.e. one lecture in a week. See also: structure of Master Informatik / Master CV / Master IM.

Introduction

Creating a Science of the Web
Tim Berners-Lee, Wendy Hall, James Hendler, Nigel Shadbolt, Daniel J. Weitzner
SCIENCE 313(11), 2006

The emerging Web of Linked Data
Chris Bizer, IEEE Intelligent Systems

Contents

The course gives an overview of web Science technologies, with emphasis on the following key aspects:

• Modeling and analysis of user behaviour and access patterns in Social Web
• Collaborative information management
• Analysis of social networks and folksonomy mining; dynamics and evolution patterns of online communities
• thematically focused search, trend analysis, information integration for Linked Open Data
• Scalable stream-oriented data analysis in the Social Web

Furthermore, we will also discuss recent research challenges and open problems in  the field of Web Science. Insofar, the special course is a good starting point for further activities related to Web Science, such as student projects, master/diploma thesis, or a future PhD study.

Organization

Exam

• Oral exam at the end of the winter semester 2009/10