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Introduction to Web Science

Online Course Materials: 

The materials of the course can be found at https://en.wikiversity.org/wiki/Web_Science

Slide decks:

The course consists of four parts.

Foundations of the Web: 

Can be found at https://en.wikiversity.org/wiki/Web_Science/Part1:_Foundations_of_the_web

Emerging Web Properties:

Can be found at https://en.wikiversity.org/wiki/Web_Science/Part2:_Emerging_Web_Properties

Behavorial Models: 

  1. Spreading Memes
  2. Herding Behaviour
  3. Socio-Economics aspects of Web
  4. Online Advertisement : 
    1. Introduction to Online Advertisement
    2. Metrics for Online Advertisement
    3. Factors impact on Advertisement Campaigns
    4. Understanding Problems with Click Fraud.
    5. Optional: Interesting reading Yu et al. Tracking the Trackers. In: Proc. of WWW 2016 ("of the top 200 news sites, as ranked by Alexa, contain at least one tracker, and at least 50% of them contain at least 11")

Web & Society: 

  1. Net Neutrality
    1. Slide deck
    2. Video
    3. Priority and Internet Quality - Jörn Kruse
  2. Copyright
    1. Slide deck
    2. Laws that choke creativity

 

Exam

Exam is in D028 on Friday, 24 February 2017, at 12:00 sharp. Do not forget to register in KLIPS. Registration is open till 17 February.
You will need 60 % of all points received during the Exercises (being held in the tutorial on Fridays) in order to be allowed to participate in the Exam

Re-Examination

Rexamination for this course for the winter term of 2016-17 will be in Room M001 on Friday, 28 April, 2017 from 14:00 hours sharp. Do not forget to register in KLIPS.  Students who have secured 60% of the total points in the exercise sessions along with those who appeared in the last exam but could not pass will only be allowed for it. 

Last year students

If you failed last years final exam you are allowed to retake it without the need of qualifying by receiving 60% of the points from the homework assignments. However we strongly suggest you work through the exercises and also take part in the lecture and tutorial as some of the content might have changed in comparison to last year and reviewing the materials on a weekly basis seems also to be usefull. 

Assignments

For the assignments, you need to make a team of 3-4people.  You can make your teams here as suggested by many students: 
https://ist.uni-koblenz.de/teams/en/user/registration/3e6c58cb -b09b-4579-a0d5-6517165bdec9 

Guidelines for submission of assignment can be found here. 

The exercises are always due Wednesdays 10 a.m.

Week Assignment Due Date Solutions Solution (Discussion)
1 Assignment 1 November 2, 2016 -  November 04, 2016
2 Assignment 2 November 9, 2016 -  November 11, 2016
3 Assignment 3 November 16, 2016 -  November 18, 2016
4 Assignment 4 November 23, 2016 -  November 25, 2016
5 Assignment 5 November 30, 2016 Solution 5 December 02, 2016
6 Assignment 6 December 07, 2016 Solution 6 December 09, 2016
7 Assignment 7 and probability functions December 14, 2016 Solution 7 December 16, 2016
8 Assignment 8 January 11, 2017 Solution 8 January 13, 2016
9 Assignment 9 January 25, 2017 Solution 9 January 30, 2017 Monday
10 Assignment 10 February 1, 2017 Solution 10 February 3, 2017
11 Assignment 11 February 08,2017 Solution 11 February 10, 2017
12 Assignment 12 February 15, 2017 Solution 12 February 17, 2017

 

Vorlesung - Introduction to Web Science

Veranstaltungsnummer: 0432026

Dozent(in) René Pickhardt
Prof. Dr. Steffen Staab
Korok Sengputa
Termin(e)
  • Mo 12.00-14.00
  • Di 12.00-14.00

Übung - Übung zu Introduction to Web Science

Veranstaltungsnummer: 0432026

Dozent(in) René Pickhardt
Prof. Dr. Steffen Staab
Korok Sengputa
Olga Zagovora
Termin(e)
  • Fr 12.00-14.00
Beteiligte: 

Prof. Dr. Steffen Staab

staab@uni-koblenz.de

Korok Sengupta

koroksengupta@uni-koblenz.de