Location Interference in Social Media for Non-Geotagged Posts in Timeline’s

Authors

  • Padma M
  • Shashikala R

Abstract

As the users of social media like twitter usage is  increasing day-to-day, especially accurate location and information of the user makes a quality success by identification of geographical location of the data by using different mediums. Foster Tweets are more powerful, more clickable, and more sharable. In this we compare the predictor variables and tackle the problem of inferring location of tweets for non geo-tagged social media analysis from prominent theoretical perspectives in several stages. Success mainly depends on high availability and accuracy, different models, and various algorithms are used by us to achieve high accuracy in inferring location of the user which are non geo tagged. In this paper we design models which are effective at inferring locations for non geo-tagged tweets, where tweets are clustered prior. Each cluster is pre-defined with locations at city level.

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Published

2020-02-21

Issue

Section

Articles