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Sentiment Analysis for E-book Reviews on Amazon to Determine E-book Impact Rank

Alsehaimi, Afnan Abdulrahman A
http://rave.ohiolink.edu/etdc/view?acc_num=dayton1619109972210567

Abstract Details

2021, Master of Computer Science (M.C.S.), University of Dayton, Computer Science.
User-generated content platforms have changed the dynamics of the business environment and redefined how organizations and governments communicate with the public. Further, such platforms act as the primary means to measure customer satisfaction. Thus, those organizations need to analyze the content generated by their customer to extract their opinions then decide based on trustable information. Also, knowing user behavior and perception for a specific product is useful to customers in the decision-making process. In this thesis, a comparative study has been conducted to develop a model to measure customer satisfaction on Amazon e-book products by applying natural language processing (NLP), machine learning, deep learning, and text mining techniques on costumers reviews. This thesis will study the possibility of generating a rating based on sentiment analysis of each product instead of rating-based stars, which is already applied to the Amazon e-book rating system.
James Buckley, Ph.D. (Committee Chair)
Saeedeh Shekarpour, Ph.D. (Committee Member)
Tam Nguyen, Ph.D. (Committee Member)
60 p.
Computer Science
Sentiment Analysis; NLP; PTA; Natural Language Processing; Ranking System

Recommended Citations

Citations

  • Alsehaimi, A. A. A. (2021). Sentiment Analysis for E-book Reviews on Amazon to Determine E-book Impact Rank [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1619109972210567

    APA Style (7th edition)

  • Alsehaimi, Afnan. Sentiment Analysis for E-book Reviews on Amazon to Determine E-book Impact Rank. 2021. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton1619109972210567.

    MLA Style (8th edition)

  • Alsehaimi, Afnan. "Sentiment Analysis for E-book Reviews on Amazon to Determine E-book Impact Rank." Master's thesis, University of Dayton, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1619109972210567

    Chicago Manual of Style (17th edition)

dayton1619109972210567
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This open access ETD is published by University of Dayton and OhioLINK.