Implementation of Classification of Geolocation of Country from Worldwide Tweets

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Jivago Mutunda Kumesa
Dr. P. R. Devale

Abstract

Social media are progressively being employed within the scientific community as key supply of knowledge to assist perceive various natural and social phenomena, and this has prompted the event of a good vary of process data processing tools that may extract data from social media for each post-hoc and real time analysis. The rise of interest in mistreatment social media as a supply for analysis has actuated braving the challenge of mechanically geo-locating tweets, given the dearth of specific location data within the majority of tweets. In distinction to abundant previous work that has targeted on location classification of tweets restricted to a selected country, here we tend to undertake the task during a broader context by classifying international tweets at the country level that is up to now undiscovered during a time period situation. We tend to analyze the extent to that a tweet’s country of origin maybe determined by creating use of eight tweet-inherent options for classification.

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