Customer Sentiment Analysis for Demand Forecasting of Electronic Devices Using Machine Learning Techniques

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Ram Chaudhari; Shreyas Umbardand; Shaunak Torgatti; Balwant Sonkamble

Customer Sentiment Analysis for Demand Forecasting of Electronic Devices Using Machine Learning Techniques

Authors: Ram Chaudhari, Shreyas Umbardand, Shaunak Torgatti, Balwant Sonkamble

Unique Paper ID: 172828
Volume: 11
Issue: 9
PageNo: 2976-2981

Keywords: Sentiment Analysis Demand Forecasting Machine Learning Natural Language Processing Electronic Devices Data-driven Decision Making

Abstract:
This paper presents a theoretical framework for predicting the demand for electronic devices by leveraging customer sentiment analysis and machine learning techniques. With the rapid evolution of electronic gadgets, forecasting market trends is crucial for staying competitive. Customer sentiment, derived from reviews and social media feedback, plays a pivotal role in predicting consumer behavior. In this work, we propose a comprehensive solution combining natural language processing (NLP) and machine learning models to predict demand trends. The proposed method offers actionable insights to enhance decisionmaking and optimize distribution strategies in the electronics industry.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 9
PageNo: 2976-2981

Customer Sentiment Analysis for Demand Forecasting of Electronic Devices Using Machine Learning Techniques

Available:https://ijirt.org/article?manuscript=172828

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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