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In recent years advent of social networking services has created large amounts of data. Microblogging website is a kind of social network in which users share short messages with others. One of the most popular microblogging services is Twitter. Every day millions of people post their opinions and sentiments in this microblog. Due to the large numbers of tweets, finding new approaches to discover...
Social media including Twitter create a space for expression and dissemination of thoughts and opinions on various topics and various events and they have created opportunity to apply theories and technology leading to search and explore the trends. Mining stream data needs to be balanced in three different branches: accuracy, time and memory. The optimal accuracy rate has obtained in the stream data...
Social media such as Twitter create space to explain the thoughts and opinions on various topics and different events, millions of users can share their ideas in this Micrblog, Therefore Twitter is converted as a source to exploration of information; make a decision and an analysis of sentiment. There is a sense in all of the texts, but it is more important to provide strategies for obtaining suitable...
Analysis of social networks will result in detection of communities and interactions between individuals. A community consists of nodes in which density of links is high. Most of existing methods presented for detecting communities, only consider the network's graph without bringing the topics into account. In this article a new method has been discussed which uses ontology and by applying clustering...
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