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) and 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 and users comment on content items. This leads to the creation of large volumes of information referred to as UGC (User Generated Content). For instance, Twitter (https://twitter.com/), known as the largest microblog service, accounts according to statistics in 2013, 500 millions users and 400 million tweets posted per day.

These user-generated contents need not only to be indexed and searched in effective and scalable ways, but they also provide a large 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 information retrieval in microblogs (Twitter). We will highlight the specificity of this type of information retrieval, and then provide current research advances in this field.