International audienceWith the explosion of Web 2.0, people are becoming more communicative through expansion of services and multi-platform applications such as microblogs, forums and social networks which establishes social and collabora-tive backgrounds. These services can be seen as very large information repository containing millions of text messages usually organized into complex networks involving users interacting with each other at specific times. Several works focused only to retrieve separate tweets or those sharing same hashtags, but, it is not powerful enough if the goal of the search is to retrieve relevant tweets based on content. In addition, finding good results concerning the given subjects needs to consider the entire context. However, context can be derived from user interactions. In this work, we propose a new method to retrieval conversation on microblogging sites. It's based on content analysis and content enrichment. The goal of our method is to present a more informative result compared to conventional search engine. To valid our method, we developed the TCOND system (Twitter Conversation Detector) which offers an alternative, results to keyword search on twitter and google. We have evaluated our method on collected social network corpus related to specific subjects, and we obtained good results
International audienceGovernments are making considerable efforts in order to enhance citizens' participation in their decision-making and policy processes. In order to understand the citizens' needs, the decision makers need to know more about citizens' behaviors, preferences and ability to use e-government online services. Recently, social media represents a strategic opportunity that can help governments to become more transparent by providing citizens with better services and enhancing information's access in a way that makes them more involved. In this paper, we propose a new conceptual framework that investigates users and communities' profiles based on social media. The aim of this paper is to explore the social citizens' profiles in order to improve and adapt public services, decision making, information sharing, transparency and collaboration enhancing...to the individual's current and relevant needs
International audienceLast years, people are becoming more communicative through expansion of services and multi-platform applications such as blogs, forums and social networks which establishes social and collabo-rative backgrounds. These services like Twitter, which is the main domain used in our work can be seen as very large information repository containing millions of text messages usually organized into complex networks involving users interacting with each other at specific times. Several works have proposed tools for tweets search focused only to retrieve the most recent but relevant tweets that address the information need. Therefore, users are unable to explore the results or retrieve more relevant tweets based on the content and may get lost or become frustrated by the information overload. In addition, finding good results concerning the given subjects needs to consider the entire context. However, context can be derived from user interactions. In this work, we propose a new method to retrieval conversation on mi-croblogging sites. It's based on content analysis and content enrichment. The goal of our method is to present a more informative result compared to conventional search engine. The proposed method has been implemented and evaluated by comparing it to Google and Twitter Search engines and we obtained very promising results
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