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Event Detection from Social Media Using Machine Learning
Published in Springer Science and Business Media Deutschland GmbH
Volume: 690
Pages: 539 - 548
Social media networks are becoming a new reliable source of information and news in recent days. Lots of opportunities are provided by social media. Social media provides all the necessary information required for event detection from text and images, identification of key posts and posters and devising a warning system in case of disasters. Event detection in social media is one of the important tasks in computer field. It facilitates in developing preventive measures for the companies. The event detection is gathering attention because social media is getting popular day by day. The approaches that have been proposed don’t represent the social network in a complete manner. Notable changes can be made in the social network’s context by defining an event as occurrence with enough momentum and force. Thus, our motive is to detect an event based on its necessary characteristics. This paper describes different types of event detection methods that have been proposed to find out hot events, key posts, and influential posters. Also, various models have been described for analysis of data coming from social media. © 2021, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetLecture Notes in Electrical Engineering
PublisherData powered by TypesetSpringer Science and Business Media Deutschland GmbH