Customer Feedback Analysis Using Aspect Based Sentiment Analysis and Fuzzy Analytic Hierarchy Process

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3ARZVXRE4H" target="_blank" >RIV/00216208:11320/25:RZVXRE4H - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196843999&doi=10.1109%2fI2CT61223.2024.10544032&partnerID=40&md5=8205d0d3973c5bf416f0a3299e036e22" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196843999&doi=10.1109%2fI2CT61223.2024.10544032&partnerID=40&md5=8205d0d3973c5bf416f0a3299e036e22</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/I2CT61223.2024.10544032" target="_blank" >10.1109/I2CT61223.2024.10544032</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Customer Feedback Analysis Using Aspect Based Sentiment Analysis and Fuzzy Analytic Hierarchy Process

Popis výsledku v původním jazyce

Customer feedback analysis has become crucial in the area of business analytics in recent years. Proper assessment of customers' perception of products and services helps organizations make data-driven decisions and maintain a competitive edge. In this article, we have developed a decision support framework to help consumers make informed choices, using Natural Language Processing (NLP) on customer feedback. Our proposed technique first uses Aspect-based Sentiment Analysis (ABSA)to identify key features and the corresponding sentiments. We have used Bi-directional Encoder Representations from Transformers (BERT) to derive sentiment scores for different criteria across different alternatives. Then, a multi-criteria decision-making (MCDM) technique such as Fuzzy Analytical Hierarchy Process (FAHP) is used for ranking of preferred alternatives. The framework is demonstrated using a case study on customer opinions shared on social media about several airlines. © 2024 IEEE.

Název v anglickém jazyce

Customer Feedback Analysis Using Aspect Based Sentiment Analysis and Fuzzy Analytic Hierarchy Process

Popis výsledku anglicky

Customer feedback analysis has become crucial in the area of business analytics in recent years. Proper assessment of customers' perception of products and services helps organizations make data-driven decisions and maintain a competitive edge. In this article, we have developed a decision support framework to help consumers make informed choices, using Natural Language Processing (NLP) on customer feedback. Our proposed technique first uses Aspect-based Sentiment Analysis (ABSA)to identify key features and the corresponding sentiments. We have used Bi-directional Encoder Representations from Transformers (BERT) to derive sentiment scores for different criteria across different alternatives. Then, a multi-criteria decision-making (MCDM) technique such as Fuzzy Analytical Hierarchy Process (FAHP) is used for ranking of preferred alternatives. The framework is demonstrated using a case study on customer opinions shared on social media about several airlines. © 2024 IEEE.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

IEEE Int. Conf. Converg. Technol., I2CT

ISBN

979-835039447-4

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

1-6

Název nakladatele

Institute of Electrical and Electronics Engineers Inc.

Místo vydání

—

Místo konání akce

Pune

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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