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  Published Paper Details:

  Paper Title

AUTOMATED CUSTOMER OPINION MINING USING LEXICON BASED APPROACH SENTIMENT ANALYSIS

  Authors

  1Letticia Tendai Tagwira,  Chiedza Hwata,  Trevor Makausi,  Wellington Makondo,  Wellington Manjoro

  Keywords

Sentiment Analysis, Opinion Mining, Lexicon Based, Semantic, Sentiment Classification

  Abstract


In our daily lives, we take our friends opinions and sometimes influenced by them in our decision making process. Any kind of organization usually makes use of suggestion box to ascertain how its stakeholders feel about their services, but few people make use of it. More people are using internet on a daily basis, the researchers developed an internet based system to enable stakeholders to input their opinions. Sentiment analysis has been used to evaluate the stakeholder�s comments. Vadersharp was used as the basis for opinions, which is a common lexicon that contains data that have the same semantic meaning or sense across different domains. The opinions are analyzed and classified into positive, negative or neutral sentiment. Sentiment analysis computationally analyses the public emotions and attitude towards a particular subject. It is useful in monitoring business operations as it allows decision makers to gain an insight of the public opinion behind certain topics.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2101296

  Paper ID - 201352

  Page Number(s) - 2429-2434

  Pubished in - Volume 9 | Issue 1 | January 2021

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  1Letticia Tendai Tagwira,  Chiedza Hwata,  Trevor Makausi,  Wellington Makondo,  Wellington Manjoro,   "AUTOMATED CUSTOMER OPINION MINING USING LEXICON BASED APPROACH SENTIMENT ANALYSIS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.9, Issue 1, pp.2429-2434, January 2021, Available at :http://www.ijcrt.org/papers/IJCRT2101296.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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