Information Retrieval and Social Media

摘要

The social Web (Web 2.0) changed the way people communicate, now a large number of online tools and platforms, such as participative encyclopedias (e.g., wikipedia.org), social bookmarking platforms (e.g., connotea.org from the Nature Publishing Group), public debate platforms (e.g., agoravox.fr), photo sharing platforms (e.g., flickr.com), micro blogging platforms (e.g., blogger.com, twitter.com), allow people to interact and to share contents. These tools provide to users the ability to express their opinions, to share content (photos, blog posts, videos, bookmarks, etc.); to connect with other users, either directly or via common interests often reflected by shared content; to add free-text tags or keywords to content; users comment on content items. All these user-generated contents need not only to be indexed and searched in effective and scalable ways, but they also provide a huge number of meaningful data, metadata that can be used as clues of evidences in a number of tasks related particularly to information retrieval. Indeed, these user-generated contents have several interesting properties, such as diversity, coverage and popularity that can be used as wisdom of crowds in search process. This talk will provide an overview of this research field. We particularly describe some properties and specificities of these data, some tasks that handle these data, we especially focus on two tasks namely searching in social media (ranking models for social IR, (micro)blog search, forum search, real time social search ) and exploiting social data to improve a search.