A multimodal approach of sentiment analysis to predict customer emotions towards a product

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

Bibliographic Details
Main Authors:	Islam, Shadman, Rahman, Moshiur, Ali, Samina Tuz Zohura, Shahrior, Tawhid
Other Authors:	Akhond, Mostafijur Rahman
Format:	Thesis
Language:	en_US
Published:	Brac University 2020
Subjects:	Product market XGBoost Sentiment Analysis
Online Access:	http://hdl.handle.net/10361/14062

id	10361-14062
record_format	dspace
spelling	10361-140622022-01-26T10:13:19Z A multimodal approach of sentiment analysis to predict customer emotions towards a product Islam, Shadman Rahman, Moshiur Ali, Samina Tuz Zohura Shahrior, Tawhid Akhond, Mostafijur Rahman Department of Computer Science and Engineering, Brac University Product market XGBoost Sentiment Analysis This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019. Cataloged from PDF version of thesis. Includes bibliographical references (pages 50-52). Begun roughly a decade ago, Sentiment analysis, the science of understanding human emotions, can trace its roots back to the middle of the 19th century. The motive of sentiment analysis is to extract and predict human emotions through facial expressions, speech or even text in some cases. Being inspired by the existing ideas, we propose a multi-modal model in the market that uses both facial cue and speech to forecast customers’ sentiments and satisfaction towards a certain product. Our model helps various companies get key insights for specific market regions and their customers, and to gain a competitive advantage over the other. In this study, we estimate product perception of a demography based on emotions that were extracted from customers’ facial expressions and speech. Although many researches have been made in the eld, but very few of them are multifaceted, integrated systems, where the different components rely on each other to produce an absolute result. We extract the emotions of people by recording their facial cues and speech patterns as they interact with a specific product of the market, such as a mobile phone in our case. We analyzed their facial expressions using AWS Rekognition. For the textual part, we analyze the sentiments using an algorithm which has a mixture of Tensorflow, Keras, Sequential model and RNN. Finally, we merge the previously obtained emotions from the video section with the textual sentiment to get the features for our predictive model. The model was generated using an algorithm named XGBoost. We have achieved an average accuracy of 81 percent approximately with 0.065 standard deviation by implementing cross validation of k-fold nature with folds of 3 and also 5 different iterations. Shadman Islam Moshiur Rahman Samina Tuz Zohura Ali Tawhid Shahrior B. Computer Science 2020-10-18T06:23:34Z 2020-10-18T06:23:34Z 2019 2019-12 Thesis ID: 16101304 ID: 19341028 ID: 19141018 ID: 19341026 http://hdl.handle.net/10361/14062 en_US Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 52 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	en_US
topic	Product market XGBoost Sentiment Analysis
spellingShingle	Product market XGBoost Sentiment Analysis Islam, Shadman Rahman, Moshiur Ali, Samina Tuz Zohura Shahrior, Tawhid A multimodal approach of sentiment analysis to predict customer emotions towards a product
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.
author2	Akhond, Mostafijur Rahman
author_facet	Akhond, Mostafijur Rahman Islam, Shadman Rahman, Moshiur Ali, Samina Tuz Zohura Shahrior, Tawhid
format	Thesis
author	Islam, Shadman Rahman, Moshiur Ali, Samina Tuz Zohura Shahrior, Tawhid
author_sort	Islam, Shadman
title	A multimodal approach of sentiment analysis to predict customer emotions towards a product
title_short	A multimodal approach of sentiment analysis to predict customer emotions towards a product
title_full	A multimodal approach of sentiment analysis to predict customer emotions towards a product
title_fullStr	A multimodal approach of sentiment analysis to predict customer emotions towards a product
title_full_unstemmed	A multimodal approach of sentiment analysis to predict customer emotions towards a product
title_sort	multimodal approach of sentiment analysis to predict customer emotions towards a product
publisher	Brac University
publishDate	2020
url	http://hdl.handle.net/10361/14062
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A multimodal approach of sentiment analysis to predict customer emotions towards a product

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