• Ruhina Syed M
• Dr. B. M. Patil

Social media is a platform to express once view in a real time. This real time view of social media makes in an attractive tool for determining automatically the user’s country of origin and /or as a proxy for the former the location from which tweets have been posted. Most of the previous research in inferring tweet geo-location has classified tweets by location within a limited geographical area or country; here we overcame the task in a broader context by classifying global tweets at the country level in a real-time scenario. The characterization of tweets is done based on utilizing geo-location. With the enthusiasm for utilizing internet-based life as the hotspot for research has inspired handling the test of naturally geo-finding tweets. To break down the tweet's nation of root this can be controlled by utilizing some tweet-inalienable highlights and Streaming LDA calculation for arrangement. Picking a fitting mix of both tweet substance and metadata can really prompt significant enhancements. We also work on finding the location of posted tweet commented by user and sentiment analysis on that comments, means we given a feedback on comment posted.

"CLASSIFICATION OF WORLDWIDE TWEETS BASED ON COUNTRY-LEVEL LOCATION CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.506-512, June 2019, Available :http://www.jetir.org/papers/JETIR1906Z71.pdf

"CLASSIFICATION OF WORLDWIDE TWEETS BASED ON COUNTRY-LEVEL LOCATION CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp506-512, June 2019, Available at : http://www.jetir.org/papers/JETIR1906Z71.pdf