Stemming and Lemmatization of Tweets for Sentiment Analysis using R
Swati Sharma1, Mamta Bansal2
1Swati Sharma, Ph.D pursuing from Shobhit University, A.P. at M.I.E.T., Meerut, India
2Dr. Mamta Bansal, C.S., Shobhitt University, Meerut, India.
Manuscript received on 16 March 2019 | Revised Manuscript received on 21 March 2019 | Manuscript published on 30 July 2019 | PP: 2038-2040 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2157078219/19©BEIESP | DOI: 10.35940/ijrte.B2157.078219
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: In our digital India, the use of social media like twitter, blogs and various forums is growing with the rapid rate. Thus the size of the data is becoming big day by day and in the span of this type of high varied and volume data, manual analysis would be a clumsy job. So, there is an alarming rate to analyze that large amount of data to make it suitable for analysis purpose. As a most elaborate open source platform, R has immeasurable user communities that thrives and perpetuate a huge amount of text analysis packages. So, in this paper we are analyzing movie related tweets using machine learning in R.
Index Terms: BOW, Linear Classifier, NLP, Rule based Classifier.
Scope of the Article: Analysis of Algorithms and Computational Complexity