Module Import 04IN2026 - Introduction to Web Science

Status: Published
Workload8 ECTS = 240 hrs
Credits, Weight8 ECTS, (n.s.)
Language of Instruction English
Semester (n.s.)
Duration1 Sem.
M/E Mandatory
Courses
Course No. Type Name MA/EL Workload Credits Contact Hours Selfstudy Group Size
04IN2026-1 Lecture Introduction to Web Science MA 6 ECTS = 180 hrs 6 ECTS 4 hrs/week = 60 hrs 120 hrs 70
04IN2026-2 Seminar/Exercise Introduction to Web Science MA 2 ECTS = 60 hrs 2 ECTS 2 hrs/week = 30 hrs 30 hrs 35
Learning Outcomes

The student should acquire an understanding of the Web as a complex socio-technical system. He should be able to relate problems and opportunities incurred in this system to the technical, social and economical foundations of the Web. He should be capable of choosing different research methods suitable for various challenges in understanding and engineering the Web.

Content

(not specified)

04IN2026-1 - Introduction to Web Science
  • History of the Web
    • Pre-Web: Memex, Hypertext, Internet, usenet, ftp, gopher
    • Web 1.0, Web 2.0, Web 3.0
    • Social and economic growth
  • Web Science and Web Science Methodologies
    • Descriptive, prescriptive, normative scientific methods:
      • What are descriptions and models of the Web?
      • What are the prerequisities for specific objectives (e.g. no government by single institution)?
    • Quantitative analytical and predictive methods
    • Simulation
  • Web Architecture and Major Applications
    • http, HTML, Internet, web server, browser, transactions
    • User generated content, blogs, wikis, folksonomies, social networks
    • Semantic Web summary: XML, RDF, OWL, microformats, microdata
    • Web security
  • Web Government
    • Institutions: W3C, IETF, ICANN
    • Government: Privacy laws, Copyright laws
    • Principles and attacks: net neutrality, censorship
  • Web Content
    • Media and standards
    • Language and cultural diversity
    • Generative models
    • Rhethoric models in the Web
    • Web annotations (Tagging, metadata, Rich Snippets)
  • Web and User Behavior/HCI
    • Navigation behavior
    • Search behavior
    • Recommendations
  • Web and Social Behavior
    • Web reflecting social behavior
    • Web affecting social behavior
  • Web Structure
    • Link Structure, small world
    • Social network sites
    • Blogosphere
  • Web Analysis
    • Web measurements (size, performance,…)
    • Crawlers
    • Search engines
    • Web archiving
  • Web Economics
    • Advertisement, including cross site advertisements and search
    • Auctioning in search and online auctions
Teaching Methods

(not specified)

Prerequisites

Basic understanding of computer science as is taught in a type-2 bachelor programme. Expected knowledge will include basic capabilities of programming in a language like Java or C, algorithmic understanding, knowledge about basic data structures and basic internet networking.

Examination Methods

 

Oral or written exam depending on class size.

Successful participation in the tutorial is a prerequisite for admission to the examination.

Credit Requirements

(not specified)

References

(not specified)

04IN2026-1 - Introduction to Web Science

Brügger, Niels (2010). Web History. Peter Lang.

Tim Berners-Lee and Mark Fischetti, Weaving the Web, 1999.

Lawrence Lessigund Jonathan Zittrain. The Future of the Internet - And How to Stop It. Yale University Press, 2008/2009

Tim Berners-Lee, Wendy Hall, James A. Hendler, Kieron O’Hara, Nigel Shadbolt, Daniel J. Weitzner. A Framework for Web Science. Foundations and Trends in Web Science, Now Publishers, 1(1), 2006; DOI: 10.1561/1800000001.

Use of this Module
  1. unmodified as Mandatory  -    BSc Computer Science 2017  -    Mandatory elective courses Computer Science  -    Introduction to Web Science
  2. unmodified as Mandatory  -    BSc Computational Visualistics 2017  -    Mandatory elective courses Computer Science  -    Introduction to Web Science
  3. unmodified as Mandatory  -    BSc Computational Visualistics 2017  -    Mandatory elective courses in Computational Visualistics or computer science  -    Introduction to Web Science
  4. unmodified as Mandatory  -    BSc Information Systems 2017  -    Mandatory elective courses Computer Science  -    Introduction to Web Science
  5. unmodified as Mandatory  -    MSc Computer Science 2017  -    Mandatory elective courses Computer Science  -    Introduction to Web Science
  6. unmodified as Mandatory  -    MSc Computer Science 2017  -    Major subject computer science  -    Data and Knowledge Engineering  -    Introduction to Web Science
  7. unmodified as Mandatory  -    MSc Computational Visualistics 2017  -    Mandatory elective courses Computer Science  -    Introduction to Web Science
  8. unmodified as Mandatory  -    MSc Computational Visualistics 2017  -    Mandatory elective courses in Computational Visualistics or computer science  -    Introduction to Web Science
  9. unmodified as Mandatory  -    MSc E-Government 2017  -    Mandatory elective courses Information Systems  -    Introduction to Web Science
  10. unmodified as Mandatory  -    MSc Information Systems 2017  -    Mandatory elective courses Application Systems in Business and Administration  -    Introduction to Web Science
  11. unmodified as Mandatory  -    MSc Web Science 2017  -    Foundations of web science  -    Introduction to Web Science
Responsible / Organizational Unit
Staab, Steffen / Institute for Computer Science
Additional Information

(not specified)

Last change
Apr 24, 2018 by Frey, Johannes
Last Change Module
May 5, 2016 by Frey, Johannes