4.7 Article

Detecting fake reviews through topic modelling

Related references

Note: Only part of the references are listed.
Article Business

Creating and detecting fake reviews of online products

Joni Salminen et al.

Summary: The study found that machines are more suitable for detecting fake reviews than humans, as machine classifiers can almost perfectly accomplish this task. The detection of fake reviews has important implications for consumer protection, competition defense for firms, and the responsibility of review platforms.

JOURNAL OF RETAILING AND CONSUMER SERVICES (2022)

Review Computer Science, Artificial Intelligence

A fake review identification framework considering the suspicion degree of reviews with time burst characteristics

Ning Wang et al.

Summary: With the rapid development of e-commerce, two-dimensional time series analysis has become increasingly important in determining fake reviews. This paper proposes a comprehensive fake review identification framework that combines suspicion degree, review text, and reviewer behavior features, with experimental results demonstrating its effectiveness.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

Article Operations Research & Management Science

Strategic information sharing in online retailing under a consignment contract with revenue sharing

Tatyana Chernonog

Summary: This study develops a model of a two-echelon supply chain involving a dominant retailer and a manufacturer with a consignment contract. The research explores the interaction and information-sharing strategies between the two parties, finding that the optimal decision regarding information sharing varies depending on the specific circumstances.

ANNALS OF OPERATIONS RESEARCH (2021)

Article Business

Exploring healthcare/health-product ecommerce satisfaction: A text mining and machine learning application

Swagato Chatterjee et al.

Summary: This study examines the impact of service aspects and emotions on customer satisfaction in healthcare/health-product e-commerce using a large dataset of online reviews. The findings provide insights for the industry and offer recommendations for improved service design and delivery for e-commerce managers.

JOURNAL OF BUSINESS RESEARCH (2021)

Review Information Science & Library Science

Fake Reviews or Not: Exploring the relationship between time trend and online restaurant reviews

Sunyoung Hlee et al.

Summary: Online reviews of newly opened restaurants exhibit a time trend with fewer negative sentiments compared to long-running restaurants. The study presents five major core propositions and five sub propositions to advance hypotheses.

TELEMATICS AND INFORMATICS (2021)

Article Computer Science, Information Systems

Resampling imbalanced data to detect fake reviews using machine learning classifiers and textual-based features

Gregorius Satia Budhi et al.

Summary: The study suggests that dynamic random sampling techniques based on textual features can improve the accuracy of fake review detection by solving the issue of class imbalance. Adaptive Boosting ensemble model is found to be superior for smaller datasets, while ensemble models show insignificant performance improvement compared to single classifiers for larger datasets.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

Article Engineering, Biomedical

Development of Integrated Neural Network Model for Identification of Fake Reviews in E-Commerce Using Multidomain Datasets

Saleh Nagi Alsubari et al.

Summary: Online product reviews have a significant impact on the success or failure of E-commerce businesses, with fake reviews potentially causing financial loss. The proposed methodology combines CNN and LSTM models to detect fake reviews. Experimental results show that the model achieved accuracies of 77%-87% and 89% in in-domain and cross-domain experiments, respectively, outperforming existing methods.

APPLIED BIONICS AND BIOMECHANICS (2021)

Proceedings Paper Computer Science, Artificial Intelligence

Sentiment Analysis on COVID Tweets: An Experimental Analysis on the Impact of Count Vectorizer and TF-IDF on Sentiment Predictions using Deep Learning Models

Ghulam Musa Raza et al.

Summary: Due to the higher popularity and excessive use of social media, COVID-19 has become the talk of the town since 2019, causing stress, anxiety, and depression worldwide. In this article, we experimented with different classifiers on COVID data to train deep neural networks using two word embedding techniques: Count Vectorizer and TF-IDF. We found that TF-IDF is more efficient in cases of large datasets, but Count Vectorizer outperforms in accuracy by 10% on Single Layer Perceptron in the context of covid19 tweets.

2021 INTERNATIONAL CONFERENCE ON DIGITAL FUTURES AND TRANSFORMATIVE TECHNOLOGIES (ICODT2) (2021)

Review Computer Science, Information Systems

Fake Reviews Detection: A Survey

Rami Mohawesh et al.

Summary: User reviews are crucial in e-commerce but fake reviews have become a significant issue. Investigating existing datasets, feature extraction techniques, and identification methods can help businesses detect fake reviews and improve profitability.

IEEE ACCESS (2021)

Review Business

Fake news, social media and marketing: A systematic review

Giandomenico Di Domenico et al.

Summary: Policy makers, managers, and academic researchers are increasingly concerned about the role of social media in spreading "Fake News". While research has focused on the implications of fake news for political communication, there is less focus on its impact on marketing and consumers. Understanding of fake news through a consumer lens is lacking, and an interdisciplinary systematic review of relevant literature identifies five themes explaining the phenomenon. A theoretical framework proposing relationships between themes and research propositions is suggested to guide future research in this area.

JOURNAL OF BUSINESS RESEARCH (2021)

Article Business

When a luxury brand bursts: Modelling the social media viral effects of negative stereotypes adoption leading to brand hate

Eleonora Pantano

Summary: This study examines the viral effects of a luxury marketing campaign using negative stereotypes on social media, revealing that negative consumer evaluations can lead to significant brand damage.

JOURNAL OF BUSINESS RESEARCH (2021)

Article Economics

Recurrent Neural Networks for Time Series Forecasting: Current status and future directions

Hansika Hewamalage et al.

Summary: Although Recurrent Neural Networks (RNNs) have shown competitive forecasting performance, they are not always superior to established statistical models such as exponential smoothing (ETS) and autoregressive integrated moving average (ARIMA).

INTERNATIONAL JOURNAL OF FORECASTING (2021)

Article Psychology, Multidisciplinary

Customer experiences in the age of artificial intelligence

Nisreen Ameen et al.

Summary: This study analyzes the impact of AI integration in shopping on customer experience, proposing a theoretical model and conducting an online survey with 434 responses. Findings suggest trust and perceived sacrifice mediate the effects of convenience, personalization, and service quality, while relationship commitment has a significant direct effect on AI-enabled customer experience. This research contributes to understanding the role of trust, perceived sacrifice, and relationship commitment in AI-enabled customer experiences.

COMPUTERS IN HUMAN BEHAVIOR (2021)

Article Business

Ulterior motives in peer and expert supplementary online reviews and consumers' perceived deception

Umar Iqbal Siddiqi et al.

Summary: This study explores the impact of ulterior motives in peer and expert supplementary online hotel reviews on consumers' perceived deception, dissatisfaction, altruistic response, and repurchase intentions. It also considers the moderating role of hotel attribute performance on perceived deception. The findings highlight the importance of addressing ethical concerns in online hotel reviews and suggest implications for hotel and travel websites as well as hoteliers.

ASIA PACIFIC JOURNAL OF MARKETING AND LOGISTICS (2021)

Review Computer Science, Artificial Intelligence

Fake consumer review detection using deep neural networks integrating word embeddings and emotion mining

Petr Hajek et al.

NEURAL COMPUTING & APPLICATIONS (2020)

Article Computer Science, Interdisciplinary Applications

Fake opinion detection: how similar are crowdsourced datasets to real data?

Tommaso Fornaciari et al.

LANGUAGE RESOURCES AND EVALUATION (2020)

Article Computer Science, Theory & Methods

A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities

Xinyi Zhou et al.

ACM COMPUTING SURVEYS (2020)

Article Engineering, Electrical & Electronic

Novel suboptimal approaches for hyperparameter tuning of deep neural network [under the shelf of optical communication]

M. A. Amirabadi et al.

PHYSICAL COMMUNICATION (2020)

Article Hospitality, Leisure, Sport & Tourism

Unveiling the cloak of deviance: Linguistic cues for psychological processes in fake online reviews

Lin Li et al.

INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT (2020)

Review Computer Science, Artificial Intelligence

Integrated topic modeling and sentiment analysis: a review rating prediction approach for recommender systems

Anbazhagan Mahadevan et al.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES (2020)

Article Business

Co-creating social media agility to build strong customer-firm relationships

Shu-Hui Chuang

INDUSTRIAL MARKETING MANAGEMENT (2020)

Article Computer Science, Artificial Intelligence

Sentiment analysis based on rhetorical structure theory:Learning deep neural networks from discourse trees

Mathias Kraus et al.

EXPERT SYSTEMS WITH APPLICATIONS (2019)

Article Computer Science, Software Engineering

Towards understanding and detecting fake reviews in app stores

Daniel Martens et al.

EMPIRICAL SOFTWARE ENGINEERING (2019)

Article Computer Science, Information Systems

A framework for fake review detection in online consumer electronics retailers

Rodrigo Barbado et al.

INFORMATION PROCESSING & MANAGEMENT (2019)

Article Business

Unfolding the characteristics of incentivized online reviews

Ana Costa et al.

JOURNAL OF RETAILING AND CONSUMER SERVICES (2019)

Article Communication

Priming and Fake News: The Effects of Elite Discourse on Evaluations of News Media

Emily Van Duyn et al.

MASS COMMUNICATION AND SOCIETY (2019)

Article Criminology & Penology

Online deception and situations conducive to the progression of non-payment fraud

David Maimon et al.

JOURNAL OF CRIME & JUSTICE (2019)

Review Computer Science, Artificial Intelligence

An unsupervised topic-sentiment joint probabilistic model for detecting deceptive reviews

Lu-yu Dong et al.

EXPERT SYSTEMS WITH APPLICATIONS (2018)

Article Communication

How People Evaluate Online Reviews

David C. DeAndrea et al.

COMMUNICATION RESEARCH (2018)

Article Business

Online Reputation Mechanisms and the Decreasing Value of Chain Affiliation

Brett Hollenbeck

JOURNAL OF MARKETING RESEARCH (2018)

Review Business

Manufactured opinions: The effect of manipulating online product reviews

Mengzhou Zhuang et al.

JOURNAL OF BUSINESS RESEARCH (2018)

Review Engineering, Industrial

Welfare economics of review information: Implications for the online selling platform owner

Tao Zhang et al.

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS (2017)

Article Computer Science, Information Systems

Product-Related Deception in E-Commerce: A Theoretical Perspective

Xiao et al.

MIS QUARTERLY (2017)

Proceedings Paper Computer Science, Information Systems

Multi-aspect Feature based Neural Network Model in Detecting Fake Reviews

Ning Luo et al.

2017 4TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE) (2017)

Proceedings Paper Computer Science, Interdisciplinary Applications

Optimize Recommendation System with Topic Modeling and Clustering

Qianqiao Liang et al.

2017 IEEE 14TH INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING (ICEBE 2017) (2017)

Article Hospitality, Leisure, Sport & Tourism

There's a troll on the information bridge! An exploratory study of deviant online behaviour impacts on tourism cosmopolitanism

Aaron Tham et al.

TOURISM RECREATION RESEARCH (2017)

Article Psychology, Multidisciplinary

The Nonverbal Communication of Positive Emotions: An Emotion Family Approach

Disa A. Sauter

EMOTION REVIEW (2017)

Article Business

An Investigation of Brand-Related User-Generated Content on Twitter

Xia Liu et al.

JOURNAL OF ADVERTISING (2017)

Review Computer Science, Artificial Intelligence

Predicting the performance of online consumer reviews: A sentiment mining approach to big data analytics

Mohammad Salehan et al.

DECISION SUPPORT SYSTEMS (2016)

Article Computer Science, Information Systems

What Online Reviewer Behaviors Really Matter? Effects of Verbal and Nonverbal Behaviors on Detection of Fake Online Reviews

Dongsong Zhang et al.

JOURNAL OF MANAGEMENT INFORMATION SYSTEMS (2016)

Article Management

Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud

Michael Luca et al.

MANAGEMENT SCIENCE (2016)

Review Psychology, Multidisciplinary

Helpfulness of user-generated reviews as a function of review sentiment, product type and information quality

Alton Y. K. Chua et al.

COMPUTERS IN HUMAN BEHAVIOR (2016)

Review Business

Online Review Helpfulness: Role of Qualitative Factors

Arpita Agnihotri et al.

PSYCHOLOGY & MARKETING (2016)

Review Business

Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus

Andreas Munzel

JOURNAL OF RETAILING AND CONSUMER SERVICES (2016)

Article Biochemical Research Methods

A heuristic approach to determine an appropriate number of topics in topic modeling

Weizhong Zhao et al.

BMC BIOINFORMATICS (2015)

Article Computer Science, Information Systems

Truth and Deception at the Rhetorical Structure Level

Victoria L. Rubin et al.

JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY (2015)

Proceedings Paper Computer Science, Theory & Methods

Using Supervised Learning to Classify Authentic and Fake Online Reviews

Snehasish Banerjee et al.

ACM IMCOM 2015, PROCEEDINGS (2015)

Article Business

Reviews Without a Purchase: Low Ratings, Loyal Customers, and Deception

Eric T. Anderson et al.

JOURNAL OF MARKETING RESEARCH (2014)

Article Computer Science, Artificial Intelligence

Manipulation in digital word-of-mouth: A reality check for book reviews

Nan Hu et al.

DECISION SUPPORT SYSTEMS (2011)

Article Business

eWOM overload and its effect on consumer behavioral intention depending on consumer involvement

Do-Hyung Park et al.

ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS (2008)

Article Information Science & Library Science

Self-Selection and Information Role of Online Product Reviews

Xinxin Li et al.

INFORMATION SYSTEMS RESEARCH (2008)

Review Communication

Applications of rhetorical structure theory

Maite Taboada et al.

DISCOURSE STUDIES (2006)

Review Communication

Rhetorical Structure Theory: looking back and moving ahead

Maite Taboada et al.

DISCOURSE STUDIES (2006)