Decision Support System for corporate reputation based social media listening using a cross-source sentiment analysis engine

R. Loke-, S. Pathak

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

10 Downloads (Pure)

Abstract

This paper presents a Decision Support System (DSS) that helps companies with corporate reputation (CR) estimates of their respective brands by collecting provided feedbacks on their products and services and deriving state-of-the-art key performance indicators. A Sentiment Analysis Engine (SAE) is at the core of the proposed DSS that enables to monitor, estimate, and classify clients’ sentiments in terms of polarity, as expressed in public comments on social media (SM) company channels. The SAE is built on machine learning (ML) text classification models that are cross-source trained and validated with real data streams from a platform like Trustpilot that specializes in user reviews and tested on unseen comments gathered from a collection of public company pages and channels on a social networking platform like Facebook. Such crosssource opinion analysis remains a challenge and is highly relevant in the disciplines of research and engineering in which a sentiment classifier for an unlabeled destination domain is assisted by a tagged source task (Singh and Jaiswal, 2022). The best performance in terms of F1 score was obtained with a multinomial naive Bayes model: 0,87 for validation and 0,74 for testing.
Original languageEnglish
Title of host publicationProceedings of the 12th International Conference on Data Science, Technology and Applications DATA
Pages559-567
Volume1
ISBN (Electronic)9789897586644
DOIs
Publication statusPublished - 2023
Event12th International Conference on Data Science, Technology and Applications - Rome, Italy
Duration: 11 Jul 202313 Jul 2023

Conference

Conference12th International Conference on Data Science, Technology and Applications
Country/TerritoryItaly
CityRome
Period11/07/2313/07/23

Fingerprint

Dive into the research topics of 'Decision Support System for corporate reputation based social media listening using a cross-source sentiment analysis engine'. Together they form a unique fingerprint.

Cite this