Instructor: Krishna Gummadi
Social media systems refer to online computer systems that enable users to interact, collaborate, and compete with one another at societal-scale.
Examples of social media systems include, social networking sites (Facebook & Google+), blogging and micro-blogging sites (Twitter & LiveJournal), content sharing sites (YouTube & Flickr), social bookmarking sites (Delicious & Reddit), crowd-sourced opinion sites (Yelp & eBay), and social peer production sites (Wikipedia & Amazon's Mechanical Turk).
With their rising popularity and a myriad of applications built on top of them, they have become an integral part of everyone's lives today. In this course, we will be examining the usage and design of these social media systems using an interdisciplinary approach that combines social network analysis, natural language processing, and large-scale data analytics.
Prerequisites for the course include undergraduate courses on algorithms, programming languages, and information systems. Students are also expected to be familiar with material covered in advanced undergraduate / master-level courses in data mining or machine learning.
The course assignments would require some programming effort towards analyzing networks or data. Experience in one or more of the programming language such as Java, C/C++, Python, Matlab is required.
The lecture will be given in English.
When: Lectures every Thursday from 10:00 to 12:00.
The first meeting is on April 21.
Where: room 029, E1 5 (MPI-SWS building, UdS Campus).
Tutorials: Tuesdays 14:00 to 16:00 in room 029, E 1 5.
|Mailing List for contact and announcements|
email@example.com: includes everyone involved with the course, the teaching staff as well as the students.
Important announcements, such as exam schedules and assignment deadlines, will be posted on this list.
Students can also use it to form project teams (each team should have at most two members), to discuss projects, and to exchange ideas and experience. Everyone should join and read this group mailing list daily.
To subscribe to this list, please visit https://lists.mpi-sws.org/listinfo/sma-ss16
firstname.lastname@example.org : includes all members of the teaching staff, the instructors as well as the teaching assistants. Students should use this for all communication with the course staff.
Please, email individual staff members only when the communication is personal, and is not related to the course in general.
IMPORTANT: For appearing in the examinations you need to also register in the HISPOS.
|Mid-term Exam||0% (Required to just pass it for taking the final exam)|
Online version of this book is available if you are connected to UDS/MPI network. Please click here to read the book online.
Further references will be given during the lecture.
|More information about our social computing research|