A new social media mashup approach

Abstract

Social media present a way to discover, report and share different types of events. For this reason, they are considered as a dynamic source of information which enables individuals to stay informed of all real-world events. This specificity encourages researchers to propose methods and approaches to detect events from social media. However many researchers are faced by divers challenges. This is due to the noise of data within the social media. In this paper, we propose a new approach for data retrieval and event detection, which differs from the previous ones by using the mashup concept. The proposed approach is able on the one hand to retrieve data from various social medias which have different structures. On the other hand, our approach aim to detect events with three main dimensions such as the topic, the time and the location.