Effective Mining of Unstructured Twitter Data for Detecting User Persecution
A. Afiya1, Shaik Javed Parvez2, S. Arun3
1A. Afiya, Department of Computer Science & Engineering, Vels Institute of Science Technology & Advanced Studies VISTAS, Chennai, (Tamil Nadu), India.
2Shaik Javed Parvez, Department of Computer Science & Engineering, Vels Institute of Science Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
3Dr. S. Arun, Department of Computer Science & Engineering, Vels Institute of Science Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
Manuscript received on 25 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript Published on 22 June 2019 | PP: 7-10 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C10020283S19/19©BEIESP
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© 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: With the increase in social media platform there has been heave in user spawn data. These data has generated in remarkable amount on daily basis through all micro blogging sites and most of the data are unstructured. Social media platform like Twitter has become a major platform for people to share their daily thoughts, opinions, suggestions and also pave a way for abusing other users verbally. We propose to investigate user oppression detection on twitter. In the paper we propose data mining techniques for mining unstructured twitter data and apply deep learning concept on tweets. We also present a case revise to exemplify the effectives of proposed system. In this paper we have tried to point the opportunities of future work by providing a expansive perspective on open forum for data mining.
Keywords: Data Mining, Classification Algorithm, Unstructured Data, Deep Learning.
Scope of the Article: Deep Learning.