Semantic Analysis for Machine Learning Approaches of Twitter Data
V. Laxmi Narasamma1, M. Sreedevi2
1V. Laxmi Narasamma, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
2Dr. M. Sreedevi, Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
Manuscript received on 20 June 2019 | Revised Manuscript received on 11 July 2019 | Manuscript Published on 17 July 2019 | PP: 1217-1221 | Volume-8 Issue-1C2 May 2019 | Retrieval Number: A12170581C219/2019©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 development of net innovation and its development, there can be a fantastic extent of statistics gift within the net for net clients and a splendid deal of facts is produced as well. net has become a diploma for online analyzing, buying and promoting thoughts and presenting insights. Social networking places like Twitter, fb, Google+ are fast selecting up prominence as they allow humans to percent and specific their views approximately subjects, have discourse with diverse networks, or placed up messages over the region. there has been part of paintings within the region of sentiment investigation of twitter information. This check centers for the most aspect on sentiment examination of twitter facts this is useful to dissect the records within the tweets wherein critiques are profoundly unstructured, heterogeneous and are both notable or bad, or impartial sometimes. on this paper, we deliver an outline and a near exam of present strategies for give up mining like machine getting to know and dictionary primarily based methodologies, together with evaluation measurements. the use of distinct device learning calculations like Naive Bayes, Max Entropy, and manual Vector device, we supply observe on twitter facts streams. we have were given furthermore pointed out latest difficulties and utilizations of Sentiment evaluation on Twitter.
Keywords: Twitter, Sentiment Analysis (SA), Opinion Mining, Machine Learning, Naive Bayes (NB), Maximum Entropy, Support Vector Machine (SVM).
Scope of the Article: Machine Learning