Abstract: Online discussions became increasingly widespread with the Web 2.0: no matter the distance, whether you know the person or not, you can discuss and exchange ideas with people all over the world through forums, blogs, and newsgroups. The news websites have extensively used forums in order to encourage the reader being a real participant in the information media. This paper aims at automatically extracting the celebrities from such discussions. We propose certain meta-criteria and we provide an evaluation on a dataset of 35,175 posts written by 14,443 users. The results show that one of the proposed meta-criteria succeeds in extracting celebrities and allows for further improvements.

Abstract: Analyzing the social roles inside on-line communities became a big challenge nowadays. The on-line communities formed around exchange platforms (e.g., forums) create an increasing source of data for analyzing user’s behavior. This paper proposes an exploratory analysis of communities in news website based on its sub-communities. Actually, we assume that people who participate in forum debate in news websites focus their participation in one or a very few topics (also called context) i.e., they formed the sub-communities. These sub-communities, will help us to find the contextual celebrity: the pertinent users in the sub-communities. We based our analysis on a dataset composed by 11,143 users writing more than 35,000 posts on 57 different forums grouped in 3 topics, and on social networks enriched with relations extracted from the content of the users’ posts.

Abstract: The expansion of web user roles is, nowadays, a fact due to the ability of users to interact, discuss, exchange ideas and opinions, form social networks with each other through the web. The interaction level among users leads to the appearance of several social roles which can be characterized as positions, behaviors, or virtual identities. These roles may be developed in social networks, and they keep changing and evolving over time. In this article, a survey of the state-of-the-art approaches is presented regarding the identification of roles within the context of a social network. It is shown that social roles exist as a function of each other; they appear and evolve through user interaction. Different approaches are analyzed and additional characteristics that should be taken into account during the roles analysis are discussed.

Abstract: Web forums are a huge data source. They allow people to interact with unknown individuals. Studying forums shows that the interaction is not obvious only through the structure but also through the content of the post. Taking into account this observation, we extract a social network with different kinds of relationships i.e. the structural relation, the name and the text quotations relation. We present here the promising results we obtain, and the difficulties we face while extracting the quotations in this kind of textual content. These results are obtained from real data (from two information websites) which make the validation difficult. So, we create a validation protocol composed of two steps and based on human raters. Finally, we will see the objective of this work which is understanding interactions in order to extract the social roles of individuals.

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Abstract: Forums on the Internet are an overwhelming source of knowledge considering the number of topics treated and users who participate in these discussions. This volume of data is difficult to comprehend for a person with respect for the large number of posts. Our work proposes a new formal framework for synthesizing information contained in these forums. We extract a social network that reflects reality by extracting multiple relationships between individuals (structural relationship, name and text quotation relationships). These relationships are created from the structure and the content of the discussion. Results show that discovering quotation relationships from forums is not trivial.