A systematic literature review on machine learning applications for consumer sentiment analysis using online reviews
Consumer sentiment analysis is a recent fad for social media-related applications such as
healthcare, crime, finance, travel, and in academia. Disentangling consumer perception to …
healthcare, crime, finance, travel, and in academia. Disentangling consumer perception to …
Fake online reviews: Literature review, synthesis, and directions for future research
Fake online reviews in e-commerce significantly affect online consumers, merchants, and,
as a result, market efficiency. Despite scholarly efforts to examine fake reviews, there still …
as a result, market efficiency. Despite scholarly efforts to examine fake reviews, there still …
[PDF][PDF] Data analytics for the identification of fake reviews using supervised learning
Fake reviews, also known as deceptive opinions, are used to mislead people and have
gained more importance recently. This is due to the rapid increase in online marketing …
gained more importance recently. This is due to the rapid increase in online marketing …
[PDF][PDF] Fake news: A survey of research, detection methods, and opportunities
X Zhou, R Zafarani - arXiv preprint arXiv:1812.00315, 2018 - academia.edu
arXiv:1812.00315v1 [cs.CL] 2 Dec 2018 Page 1 Fake News: A Survey of Research,
Detection Methods, and Opportunities XINYI ZHOU, Syracuse University, USA REZA …
Detection Methods, and Opportunities XINYI ZHOU, Syracuse University, USA REZA …
Fake reviews detection: A survey
In e-commerce, user reviews can play a significant role in determining the revenue of an
organisation. Online users rely on reviews before making decisions about any product and …
organisation. Online users rely on reviews before making decisions about any product and …
[HTML][HTML] Spatial prediction of landslide susceptibility in western Serbia using hybrid support vector regression (SVR) with GWO, BAT and COA algorithms
AL Balogun, F Rezaie, QB Pham, L Gigović… - Geoscience …, 2021 - Elsevier
In this study, we developed multiple hybrid machine-learning models to address parameter
optimization limitations and enhance the spatial prediction of landslide susceptibility models …
optimization limitations and enhance the spatial prediction of landslide susceptibility models …
Deep learning to filter SMS Spam
The popularity of short message service (SMS) has been growing over the last decade. For
businesses, these text messages are more effective than even emails. This is because while …
businesses, these text messages are more effective than even emails. This is because while …
Sentiment analysis using deep learning approaches: an overview
Nowadays, with the increasing number of Web 2.0 tools, users generate huge amounts of
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …
Robust spammer detection using collaborative neural network in Internet-of-Things applications
Spamming is emerging as a key threat to the Internet of Things (IoT)-based social media
applications. It will pose serious security threats to the IoT cyberspace. To this end, artificial …
applications. It will pose serious security threats to the IoT cyberspace. To this end, artificial …
A deep learning approach for detecting fake reviewers: Exploiting reviewing behavior and textual information
Ensuring the credibility of online consumer reviews (OCRs) is a growing societal concern.
However, the problem of fake reviewers on online platforms significantly influences e …
However, the problem of fake reviewers on online platforms significantly influences e …