IR in Social Media (IRSM)
author: Matthew Hurst, Microsoft Live Labs, Microsoft
published: Nov. 4, 2008, recorded: September 2008, views: 4607
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
We define Social Media as a user-generated content on a Web. Social Media includes but not limited to: blogs, usenet, forums. The first part of a tutorial is pretty technical and hands-on. We will show specifics of a data acquisition from blogs, microblogs, usenet. We will present our existing data sets and show how to use them. In the second part we will talk about specifics of using obtained data. We will cover keyword extraction and other data mining techniques. Spam has become a major problem for Internet users and covers web search as well as most aspects of communication including email, IM, discussion forums. The recent popularity of blogging has spurned a surge in blog spam, with many flavors including splogs, comment spam, trackback spam and ping spam. In this talk we will discuss the differences and commonalities of combating spam in the blog medium vs. other types of spam. The exposition will be supported by results and examples based on real data.
Download slides: russir08_maykov_irsm_01.pdf (1.5 MB)
Download slides: russir08_maykov_irsm_01.ppt (7.2 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !
Write your own review or comment: