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      Sentiment Analysis of Comments on Rohingya Movement with Support Vector Machine

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          Abstract

          The Rohingya Movement and Crisis caused a huge uproar in the political and economic state of Bangladesh. Refugee movement is a recurring event and a large amount of data in the form of opinions remains on social media such as Facebook, with very little analysis done on them.To analyse the comments based on all Rohingya related posts, we had to create and modify a classifier based on the Support Vector Machine algorithm. The code is implemented in python and uses scikit-learn library. A dataset on Rohingya analysis is not currently available so we had to use our own data set of 2500 positive and 2500 negative comments. We specifically used a support vector machine with linear kernel. A previous experiment was performed by us on the same dataset using the naive bayes algorithm, but that did not yield impressive results.

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          Most cited references 3

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          Performing sentiment analysis in Bangla microblog posts

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            Supervised approach of sentimentality extraction from bengali facebook status

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              Sentiment detection from Bangla text using contextual valency analysis

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                Author and article information

                Journal
                22 March 2018
                Article
                1803.08790

                http://creativecommons.org/licenses/by/4.0/

                Custom metadata
                cs.IR cs.CL cs.LG

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