Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews
With the rapid development of e-commerce, posting reviews online has become an important way for people to express their views and transfer their experience. The reviews not only assist individuals in making choices, but also assist businesses of finding valuable information to help improve the sale...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2022
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| Online Access: | https://eprints.nottingham.ac.uk/71553/ |
| _version_ | 1848800669327163392 |
|---|---|
| author | Fu, Ruidan |
| author_facet | Fu, Ruidan |
| author_sort | Fu, Ruidan |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | With the rapid development of e-commerce, posting reviews online has become an important way for people to express their views and transfer their experience. The reviews not only assist individuals in making choices, but also assist businesses of finding valuable information to help improve the sales. In order to processing the unstructured text, sentiment analysis is useful of mining opinions and sentiments. In this research, customer reviews of HUAWEI phone products on Amazon were collected to bring insights for the company. By combining the topic modeling and the dependency analysis of the reviews, the study gets a more comprehensive and more interpretable results to inform the business. |
| first_indexed | 2025-11-14T20:55:14Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-71553 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:55:14Z |
| publishDate | 2022 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-715532023-07-07T13:49:28Z https://eprints.nottingham.ac.uk/71553/ Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews Fu, Ruidan With the rapid development of e-commerce, posting reviews online has become an important way for people to express their views and transfer their experience. The reviews not only assist individuals in making choices, but also assist businesses of finding valuable information to help improve the sales. In order to processing the unstructured text, sentiment analysis is useful of mining opinions and sentiments. In this research, customer reviews of HUAWEI phone products on Amazon were collected to bring insights for the company. By combining the topic modeling and the dependency analysis of the reviews, the study gets a more comprehensive and more interpretable results to inform the business. 2022-09-08 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/71553/1/20323936_BUSI4374_2021_22.pdf Fu, Ruidan (2022) Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews. [Dissertation (University of Nottingham only)] |
| spellingShingle | Fu, Ruidan Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews |
| title | Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews |
| title_full | Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews |
| title_fullStr | Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews |
| title_full_unstemmed | Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews |
| title_short | Investigation of HUAWEI Phone Product Opinions Using Aspect Based Sentiment Analysis (ABSA) on Customer Reviews |
| title_sort | investigation of huawei phone product opinions using aspect based sentiment analysis (absa) on customer reviews |
| url | https://eprints.nottingham.ac.uk/71553/ |