相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。A systematic literature review on spam content detection and classification
Sanaa Kaddoura et al.
PEERJ COMPUTER SCIENCE (2022)
Creating and detecting fake reviews of online products
Joni Salminen et al.
JOURNAL OF RETAILING AND CONSUMER SERVICES (2022)
Fuzzy artificial bee colony-based CNN-LSTM and semantic feature for fake product review classification
Minu Susan Jacob et al.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE (2022)
Detection of spam reviews through a hierarchical attention architecture with N-gram CNN and Bi-LSTM
Yuxin Liu et al.
INFORMATION SYSTEMS (2022)
From conflicts and confusion to doubts: Examining review inconsistency for fake review detection
Guohou Shan et al.
DECISION SUPPORT SYSTEMS (2021)
Analysis of concept drift in fake reviews detection
Rami Mohawesh et al.
EXPERT SYSTEMS WITH APPLICATIONS (2021)
Fake reviews classification using deep learning ensemble of shallow convolutions
Muhammad Saad Javed et al.
JOURNAL OF COMPUTATIONAL SOCIAL SCIENCE (2021)
Fake Reviews Detection: A Survey
Rami Mohawesh et al.
IEEE ACCESS (2021)
An Ensemble Model for Fake Online Review Detection Based on Data Resampling, Feature Pruning, and Parameter Optimization
Jianrong Yao et al.
IEEE ACCESS (2021)
The Location of Maximum Emotion in Deceptive and Truthful Texts
Amir Sepehri et al.
SOCIAL PSYCHOLOGICAL AND PERSONALITY SCIENCE (2021)
Incorporating feature representation into BiLSTM for deceptive review detection
Wentao Liu et al.
COMPUTING (2020)
Fake online reviews: Literature review, synthesis, and directions for future research
Yuanyuan Wu et al.
DECISION SUPPORT SYSTEMS (2020)
Opinion spam detection: Using multi-iterative graph-based model
Shirin Noekhah et al.
INFORMATION PROCESSING & MANAGEMENT (2020)
Fake consumer review detection using deep neural networks integrating word embeddings and emotion mining
Petr Hajek et al.
NEURAL COMPUTING & APPLICATIONS (2020)
A burst-based unsupervised method for detecting review spammer groups
Shu-Juan Ji et al.
INFORMATION SCIENCES (2020)
hPSD: A Hybrid PU-Learning-Based Spammer Detection Model for Product Reviews
Zhiang Wu et al.
IEEE TRANSACTIONS ON CYBERNETICS (2020)
Generating behavior features for cold-start spam review detection with adversarial learning
Xiaoya Tang et al.
INFORMATION SCIENCES (2020)
Camouflage is NOT easy: Uncovering adversarial fraudsters in large online app review platform
Jianyu Wang et al.
MEASUREMENT & CONTROL (2020)
Exploring Thematic Coherence in Fake News
Martins Samuel Dogo et al.
ECML PKDD 2020 WORKSHOPS (2020)
A non-convex semi-supervised approach to opinion spam detection by ramp-one class SVM
Yingjie Tian et al.
INFORMATION PROCESSING & MANAGEMENT (2020)
Effective Opinion Spam Detection: A Study on Review Metadata Versus Content
Ajay Rastogi et al.
JOURNAL OF DATA AND INFORMATION SCIENCE (2020)
Illusions of truth-Experimental insights into human and algorithmic detections of fake online reviews
Daria Plotkina et al.
JOURNAL OF BUSINESS RESEARCH (2020)
Spam Review Detection Techniques: A Systematic Literature Review
Naveed Hussain et al.
APPLIED SCIENCES-BASEL (2019)
A framework for fake review detection in online consumer electronics retailers
Rodrigo Barbado et al.
INFORMATION PROCESSING & MANAGEMENT (2019)
Opinion spam detection by incorporating multimodal embedded representation into a probabilistic review graph
Yuanchao Liu et al.
NEUROCOMPUTING (2019)
An individual-group-merchant relation model for identifying fake online reviews: an empirical study on a Chinese e-commerce platform
Chuanming Yu et al.
INFORMATION TECHNOLOGY & MANAGEMENT (2019)
Learning review representations from user and product level information for spam detection
Chunyuan Yuan et al.
2019 19TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2019) (2019)
Enactment of Ensemble Learning for Review Spam Detection on Selected Features
Faisal Khurshid et al.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS (2019)
A Review Structure Based Ensemble Model for Deceptive Review Spam
Zhi-Yuan Zeng et al.
INFORMATION (2019)
How good are we at detecting deception? A review of current techniques and theories
Alicia Nortje et al.
SOUTH AFRICAN JOURNAL OF PSYCHOLOGY (2019)
Using Named Entities for Computer-Automated Verbal Deception Detection
Bennett Kleinberg et al.
JOURNAL OF FORENSIC SCIENCES (2018)
Hybrid approach of improved binary particle swarm optimization and shuffled frog leaping for feature selection
S. P. Rajamohana et al.
COMPUTERS & ELECTRICAL ENGINEERING (2018)
A unified framework for detecting author spamicity by modeling review deviation
Yuanchao Liu et al.
EXPERT SYSTEMS WITH APPLICATIONS (2018)
An unsupervised topic-sentiment joint probabilistic model for detecting deceptive reviews
Lu-yu Dong et al.
EXPERT SYSTEMS WITH APPLICATIONS (2018)
Online customer reviews and consumer evaluation: The role of review font
Yunhui Huang et al.
INFORMATION & MANAGEMENT (2018)
DRI-RCNN: An approach to deceptive review identification using recurrent convolutional neural network
Wen Zhang et al.
INFORMATION PROCESSING & MANAGEMENT (2018)
Task-specific word identification from short texts using a convolutional neural network
Shuhan Yuan et al.
INTELLIGENT DATA ANALYSIS (2018)
Detecting Review Manipulation on Online Platforms with Hierarchical Supervised Learning
Naveen Kumar et al.
JOURNAL OF MANAGEMENT INFORMATION SYSTEMS (2018)
Towards automatic filtering of fake reviews
Emerson F. Cardoso et al.
NEUROCOMPUTING (2018)
Detecting Spammer Groups From Product Reviews: A Partially Supervised Learning Model
Lu Zhang et al.
IEEE ACCESS (2018)
Is This Review Believable? A Study of Factors Affecting the Credibility of Online Consumer Reviews from an ELM Perspective
Cindy Cheung et al.
Journal of the Association for Information Systems (2018)
Towards Accurate Deceptive Opinions Detection Based on Word Order-Preserving CNN
Siyuan Zhao et al.
MATHEMATICAL PROBLEMS IN ENGINEERING (2018)
Detecting Deceptive Review Spam via Attention-Based Neural Networks
Xuepeng Wang et al.
NATURAL LANGUAGE PROCESSING AND CHINESE COMPUTING, NLPCC 2017 (2018)
Negative reviews: Formation, spread, and halt of opportunistic behavior
Saba Salehi-Esfahani et al.
INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT (2018)
Combating Crowdsourced Review Manipulators: A Neighborhood-Based Approach
Parisa Kaghazgaran et al.
WSDM'18: PROCEEDINGS OF THE ELEVENTH ACM INTERNATIONAL CONFERENCE ON WEB SEARCH AND DATA MINING (2018)
In an Absolute State: Elevated Use of Absolutist Words Is a Marker Specific to Anxiety, Depression, and Suicidal Ideation
Mohammed Al-Mosaiwi et al.
CLINICAL PSYCHOLOGICAL SCIENCE (2018)
The manager's dilemma: a conceptualization of online review manipulation strategies
Stefan Gossling et al.
CURRENT ISSUES IN TOURISM (2018)
Authentic versus fictitious online reviews: A textual analysis across luxury, budget, and mid-range hotels
Snehasish Banerjee et al.
JOURNAL OF INFORMATION SCIENCE (2017)
Detecting Deceptive Opinions: Intra and Cross-Domain Classification Using an Efficient Representation
Leticia C. Cagnina et al.
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS (2017)
Theorizing the textual differences between authentic and fictitious reviews Validation across positive, negative and moderate polarities
Snehasish Banerjee et al.
INTERNET RESEARCH (2017)
Document representation and feature combination for deceptive spam review detection
Luyang Li et al.
NEUROCOMPUTING (2017)
Revisiting Semi-Supervised Learning for Online Deceptive Review Detection
Jitendra Kumar Rout et al.
IEEE ACCESS (2017)
Automated Crowdturfing Attacks and Defenses in Online Review Systems
Yuanshun Yao et al.
CCS'17: PROCEEDINGS OF THE 2017 ACM SIGSAC CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY (2017)
Recital of Supervised Learning on Review Spam Detection: An Empirical Analysis
Faisal Khurshid et al.
2017 12TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS AND KNOWLEDGE ENGINEERING (IEEE ISKE) (2017)
Investigating the effect of quality of grammar and mechanics (QGAM) in online reviews: The mediating role of reviewer crediblity
Seth Ketron
JOURNAL OF BUSINESS RESEARCH (2017)
Improving detection of untrustworthy online reviews using ensemble learners combined with feature selection
Brian Heredia et al.
SOCIAL NETWORK ANALYSIS AND MINING (2017)
Whose online reviews to trust? Understanding reviewer trustworthiness and its impact on business
Shankhadeep Banerjee et al.
DECISION SUPPORT SYSTEMS (2017)
Semi-supervised Learning based Fake Review Detection
Huaxun Deng et al.
2017 15TH IEEE INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED PROCESSING WITH APPLICATIONS AND 2017 16TH IEEE INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING AND COMMUNICATIONS (ISPA/IUCC 2017) (2017)
CoFea: A Novel Approach to Spam Review Identification Based on Entropy and Co-Training
Wen Zhang et al.
ENTROPY (2016)
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)
What makes an online consumer review trustworthy?
Raffaele Filieri
ANNALS OF TOURISM RESEARCH (2016)
CoSpa: A Co-training Approach for Spam Review Identification with Support Vector Machine
Wen Zhang et al.
INFORMATION (2016)
Detection of review spam: A survey
Atefeh Heydari et al.
EXPERT SYSTEMS WITH APPLICATIONS (2015)
Examining the moderating role of sense of membership in online review evaluations
Chuan Luo et al.
INFORMATION & MANAGEMENT (2015)
Detecting positive and negative deceptive opinions using PU-learning
Donato Hernandez Fusilier et al.
INFORMATION PROCESSING & MANAGEMENT (2015)
Sentiment analysis: A review and comparative analysis of web services
Jesus Serrano-Guerrero et al.
INFORMATION SCIENCES (2015)
Truth and Deception at the Rhetorical Structure Level
Victoria L. Rubin et al.
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY (2015)
Learning Document Representation for Deceptive Opinion Spam Detection
Luyang Li et al.
CHINESE COMPUTATIONAL LINGUISTICS AND NATURAL LANGUAGE PROCESSING BASED ON NATURALLY ANNOTATED BIG DATA (CCL 2015) (2015)
Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-generated media and its influence on recommendation adoption and word of mouth
Raffaele Filieri et al.
TOURISM MANAGEMENT (2015)
Base Rates, Deception Detection, and Deception Theory: A Reply to Burgoon (2015)
Hee Sun Park et al.
HUMAN COMMUNICATION RESEARCH (2015)
What makes a useful online review? Implication for travel product websites
Zhiwei Liu et al.
TOURISM MANAGEMENT (2015)
Detecting Fake Review with Rumor Model-Case Study in Hotel Review
Tien Chang et al.
INTELLIGENCE SCIENCE AND BIG DATA ENGINEERING: BIG DATA AND MACHINE LEARNING TECHNIQUES, ISCIDE 2015, PT II (2015)
Linguistic characteristics of shill reviews
Toan Ong et al.
ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS (2014)
A theoretical framework to identify authentic online reviews
Snehasish Banerjee et al.
ONLINE INFORMATION REVIEW (2014)
Exploiting liars' verbal strategies by examining the verifiability of details
Galit Nahari et al.
LEGAL AND CRIMINOLOGICAL PSYCHOLOGY (2014)
Theorizing About Deception
Timothy R. Levine et al.
JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY (2014)
The effects of individualism-collectivism cultural orientation on eWOM information
Chuan Luo et al.
INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT (2014)
Spotting Fake Reviews using Positive-Unlabeled Learning
Huayi Li et al.
COMPUTACION Y SISTEMAS (2014)
The Verifiability Approach: Countermeasures Facilitate its Ability to Discriminate Between Truths and Lies
Galit Nahari et al.
APPLIED COGNITIVE PSYCHOLOGY (2014)
In eWOMWe Trust A Framework of Factors that Determine the eWOM Credibility
Bettina Lis
BUSINESS & INFORMATION SYSTEMS ENGINEERING (2013)
Impact of informational factors on online recommendation credibility: The moderating role of source credibility
Chuan Luo et al.
DECISION SUPPORT SYSTEMS (2013)
Detecting Deceptive Chat-Based Communication Using Typing Behavior and Message Cues
Douglas C. Derrick et al.
ACM TRANSACTIONS ON MANAGEMENT INFORMATION SYSTEMS (2013)
Manipulation of online reviews: An analysis of ratings, readability, and sentiments
Nan Hu et al.
DECISION SUPPORT SYSTEMS (2012)
Detecting Automation of Twitter Accounts: Are You a Human, Bot, or Cyborg?
Zi Chu et al.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING (2012)
Helpfulness of Online Consumer Reviews: Readers' Objectives and Review Cues
Hyunmi Baek et al.
INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE (2012)
Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database
Michael Anderson et al.
ECONOMIC JOURNAL (2012)
Does the Truth Come Out in the Writing? SCAN as a Lie Detection Tool
Galit Nahari et al.
LAW AND HUMAN BEHAVIOR (2012)
Coh-Metrix: Providing Multilevel Analyses of Text Characteristics
Arthur C. Graesser et al.
EDUCATIONAL RESEARCHER (2011)
Permutation importance: a corrected feature importance measure
Andre Altmann et al.
BIOINFORMATICS (2010)
Decision support for determining veracity via linguistic-based cues
Christie M. Fuller et al.
DECISION SUPPORT SYSTEMS (2009)
Credibility of Electronic Word-of-Mouth: Informational and Normative Determinants of On-line Consumer Recommendations
Man Yee Cheung et al.
INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE (2009)
Cues to deception and ability to detect lies as a function of police interview styles
Aldert Vrij et al.
LAW AND HUMAN BEHAVIOR (2007)
Strategic manipulation of Internet opinion forums: Implications for consumers and firms
Chrysanthos Dellarocas
MANAGEMENT SCIENCE (2006)
The dynamic nature of deceptive verbal communication
Judee K. Burgoon et al.
JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY (2006)
An introduction to ROC analysis
Tom Fawcett
PATTERN RECOGNITION LETTERS (2006)
The detection of deception with the reality monitoring approach: A review of the empirical evidence
J Masip et al.
PSYCHOLOGY CRIME & LAW (2005)
A comparison of classification methods for predicting deception in computer-mediated communication
L Zhou et al.
JOURNAL OF MANAGEMENT INFORMATION SYSTEMS (2004)
Automating linguistics-based cues for detecting deception in text-based asynchronous computer-mediated communication
L Zhou et al.
GROUP DECISION AND NEGOTIATION (2004)
Lying words: Predicting deception from linguistic styles
ML Newman et al.
PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN (2003)