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An Analysis of E-Commerce Identification Using Sentimental Analysis: A Survey

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Applied Computational Technologies (ICCET 2022)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 303))

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Abstract

Sentiment analysis is also known as opinion mining. It is one of the critical and rapidly growing fields in Natural Language Processing. This research is intended to address the most fundamental difficulties relating to sentiment analysis. Sentiment polarity classification. A generic technique for categorizing sentiment polarity, along with detailed processes, is presented. The input data for this project is taken from major e-commerce websites like Amazon’s product ratings. Analyses on sentence-part classification and review-part categorization have shown promising results. At last, insights will be derived from preprocessed data for future execution and how much product structure and features impact execution. Created a significant impact on improving the business by producing a quality product, gadget, or accessory that customers expect and satisfying their expectations.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, M. Kumarasamy College of Engineering, Karur, 639113, India

    P. Pandiaraja, S. Aishwarya, S. V. Indubala, S. Neethiga & K. Sanjana

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  1. P. Pandiaraja
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  2. S. Aishwarya
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  3. S. V. Indubala
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  4. S. Neethiga
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  5. K. Sanjana
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Corresponding author

Correspondence to P. Pandiaraja .

Editor information

Editors and Affiliations

  1. Department of Electronics and Telecommunication Engineering, Dr. B. A. Technological University, Lonere, Maharashtra, India

    Brijesh Iyer

  2. Department of Digital Education and Policy, Swansea University, Swansea, UK

    Tom Crick

  3. Creative Technologies and Product Design, National Taipei University of Business, Taipei City, Taiwan

    Sheng-Lung Peng

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Pandiaraja, P., Aishwarya, S., Indubala, S.V., Neethiga, S., Sanjana, K. (2022). An Analysis of E-Commerce Identification Using Sentimental Analysis: A Survey. In: Iyer, B., Crick, T., Peng, SL. (eds) Applied Computational Technologies. ICCET 2022. Smart Innovation, Systems and Technologies, vol 303. Springer, Singapore. https://doi.org/10.1007/978-981-19-2719-5_69

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