Identifying System Location Specifics based on Classification of Worldwide Tweets
Aatmakuri Hima1, Sirasanagondla Venkata Naga Sreenivasu2
1Aatmakuri Hima pursuing M.Tech. (CSE), Narasaraopet Engineering College, Narasaraopeta, AP – 522601, India.
2Dr.S.V.Naga Srinivasu, Professor, Computer science and engineering, Narasaraopeta Engineering College, Narasaraopet, AP -522601, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 5452-5454 | Volume-8 Issue-12, October 2019. | Retrieval Number: K21900981119/2019©BEIESP | DOI: 10.35940/ijitee.K2190.1081219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: As social networking sites are gaining populism across the globe, people are more enthusiastic about sharing their thoughts on Various networking Platforms. Facebook and Twitter have become a leading destination for sharing various kinds of information. In the existing literature the focus is to access the information published in the networking platforms in the real-time, and they do not focus on obtaining the geo-location of the user. Here we propose a monitoring system that classifies the tweets using some reliable techniques which can be used across the globe without any security concerns. As there is a lot of fake news available in the digital form, there is a definite need to access the user information and his geo-location metrics. In this paper, we have introduced Naive Bayes Multinomial classifier and a few other models which performs a spatiotemporal analysis. This study also identifies a comprehensive set of performance metrics which can access the tweet’s country of origin by using eight tweet-inherent features. The outcome of this analysis can be used by various cyber-crime departments to deal with the numerous cybercrime cases on networking platforms, and real-time decisive actions can be taken.
Keywords: Face Book, Geo-location, Social Networking, Real-Time, Classification, Tweets country of origin, Message Classification.
Scope of the Article: Classification