The Role of Fake Review Detection in Managing Online Corporate Reputation

R. Loke, Z. Kisoen

2022

Abstract

In a recent official statement, Google highlighted the negative effects of fake reviews on review websites and specifically requested companies not to buy and users not to accept payments to provide fake reviews (Google, 2019). Also, governmental authorities started acting against organisations that show to have a high number of fake reviews on their apps (DigitalTrends, 2018; Gov UK, 2020; ACM, 2017). However, while the phenomenon of fake reviews is well-known in industries as online journalism and business and travel portals, it remains a difficult challenge in software engineering (Martens & Maalej, 2019). Fake reviews threaten the reputation of an organisation and lead to a disvalued source to determine the public opinion about brands. Negative fake reviews can lead to confusion for customers and a loss of sales. Positive fake reviews might also lead to wrong insights about real users’ needs and requirements. Although fake reviews have been studied for a while now, there are only a limited number of spam detection models available for companies to protect their corporate reputation. Especially in times with the coronavirus, organisations need to put extra focus on online presence and limit the amount of negative input that affects their competitive position which can even lead to business loss. Given state-of-the-art derived features that can be engineered from review texts, a spam detector based on supervised machine learning is derived in an experiment that performs quite well on the well-known Amazon Mechanical Turk dataset.

Paper Citation

in Harvard Style

Loke R. and Kisoen Z. (2022). The Role of Fake Review Detection in Managing Online Corporate Reputation. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-583-8, pages 245-256. DOI: 10.5220/0011144600003269

in Bibtex Style

@conference{data22,
author={R. Loke and Z. Kisoen},
title={The Role of Fake Review Detection in Managing Online Corporate Reputation},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2022},
pages={245-256},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011144600003269},
isbn={978-989-758-583-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - The Role of Fake Review Detection in Managing Online Corporate Reputation
SN - 978-989-758-583-8
AU - Loke R.
AU - Kisoen Z.
PY - 2022
SP - 245
EP - 256
DO - 10.5220/0011144600003269