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Word Cloud and Sentiment Analysis of Amazon Earphones Reviews with R Programming Language

Author

Listed:
  • Ahmed Imran KABIR
  • Koushik AHMED
  • Ridoan KARIM

Abstract

The internet has opened a very wide range of ways for exchanging information or data. The development of internet influenced our daily lives to share our opinion on internet. We can share our opinions in social media like twitter, Facebook, LinkedIn or micro blogging site. We can give reviews about any product or we can share what things we are expecting. The sharing of information in internet makes internet a rich resource. Large organization or any type of business who want to do business in a customer centric way needs to know what peoples are thinking. To know that, we can use online resources but to analyze all the data in a short time is not easy if we try to figure out everyone is thought one by one. Sentiment analysis and word cloud in text mining is introduced to eradicate this problem. It helps to know what peoples are thinking and helps to develop the client experience and helps to take decision in a customer centric way. The project on word cloud and sentiment analysis of amazon earphones reviews is basically done to know the process which we can used in our practical life to know the people’s attitude, opinions, reviews, sentiment towards something from unstructured big data from online resources.

Suggested Citation

  • Ahmed Imran KABIR & Koushik AHMED & Ridoan KARIM, 2020. "Word Cloud and Sentiment Analysis of Amazon Earphones Reviews with R Programming Language," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 24(4), pages 55-71.
    • Handle: RePEc:aes:infoec:v:24:y:2020:i:4:p:55-71
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    Cited by:

    1. Ahmed Imran KABIR & Suraya AKTER & Sriman MITRA, 2021. "Students Engagement Detection in Online Learning During Covid-19 Pandemic Using R Programming Language," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 25(3), pages 26-37.

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