Abstract

These days, there is substantial research into predicting the position of online social media users. Research into the automated recognition of places identified or quoted in documents has been under way for decades. Twitter has attracted a vast number of users worldwide as a standout among the online social network organizations that send millions of tweets on a daily basis. Twitter's real-time nature makes it an appealing disaster relief tool, as both victims and authorities can place their concerns and remedies in real-time at the same venue. Knowing the role of a social media user and their posts is critical for various purposes, such as the recommendation of location-based products/services, locality detection of emergencies, demographic analysis, or tracking of disaster outbreaks. This paper discusses the various techniques used for predicting the user locations using the data received from Twitter.

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