Abstract: Detection of emerging topics is interest motivated by the rapid growth of social networks. Posts include not only text but also images, URLs, and videos. We focus on emergence of topics signaled by social aspects of these networks. In this system we are taking a Facebook as Social media to perform the operation, specifically. We proposing the NLP algorithm of the mentioning behavior of a social network user, and propose to detect the emergence of a new topic from the Aggregating facebook data from hundreds of users by using the Hadoop Framework. We demonstrate our technique in several real data sets we gathered from Twitter. The experiments show that the proposed KNN approaches can detect new topics at least as early as text-anomaly-based approaches, and in some cases much earlier when the topic is poorly identified by the textual contents in posts.
Keywords: Topic detection, social network such as facebook, Hadoop framework.
Title: Social Media Post Analyzer
Author: Neha Bhondwe, Nupur Chillal, Priyanka Sutar, Snehal Wakade, Shital Jadhav
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), SSN 2348-120X (online)
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