Using Social Conversational Context For Detecting Users Interactions on Microblogging Sites
| Autor: | Belkaroui, Rami, Faiz, Rim, Elkhlifi, Aymen |
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| Přispěvatelé: | Laboratoire de Recherche Opérationnelle de Décision et de Contrôle de Processus (LARODEC), Université de Tunis-ISG de Tunis, Langues, logiques, informatiques, cognition (LaLIC), Université Paris-Sorbonne (UP4)-Centre National de la Recherche Scientifique (CNRS), Belkaroui, Rami |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: | |
| Zdroj: | Revue des Nouvelles Technologies de l'Information Revue des Nouvelles Technologies de l'Information, Editions RNTI, 2015 |
| ISSN: | 1764-1667 |
| Popis: | International audience; In the current era, microblogging services like Twitter, gives people the ability to communicate, interact, collaborate with each other, reply to messages from others and create conversations. 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 have proposed tools for tweets search focused only to retrieve relevant tweets. 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 this paper, we propose a new method to retrieve conversation on microblog-ging sites particularly Twitter. 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. |
| Databáze: | OpenAIRE |
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