Computational Linguistic Models of Deceptive Opinion Spam
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[1] P. Ekman,et al. Nonverbal leakage and clues to deception. , 1969, Psychiatry.
[2] M. Spence. Job Market Signaling , 1973 .
[3] J. R. Landis,et al. The measurement of observer agreement for categorical data. , 1977, Biometrics.
[4] D. O. Sears. College sophomores in the laboratory: Influences of a narrow data base on social psychology's view of human nature. , 1986 .
[5] Donal E. Carlston,et al. Negativity and extremity biases in impression formation: A review of explanations. , 1989 .
[6] L. Joseph,et al. Bayesian estimation of disease prevalence and the parameters of diagnostic tests in the absence of a gold standard. , 1995, American journal of epidemiology.
[7] Stephen Porter,et al. The language of deceit: An investigation of the verbal clues to deception in the interrogation context , 1996 .
[8] P. Ekman,et al. The ability to detect deceit generalizes across different types of high-stake lies. , 1997, Journal of personality and social psychology.
[9] Andrei Z. Broder,et al. On the resemblance and containment of documents , 1997, Proceedings. Compression and Complexity of SEQUENCES 1997 (Cat. No.97TB100171).
[10] Marcia K. Johnson,et al. False memories and confabulation , 1998, Trends in Cognitive Sciences.
[11] Thorsten Joachims,et al. Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.
[12] Mark A. deTurck,et al. The Behavioral Correlates of Sanctioned and Unsanctioned Deceptive Communication , 1998 .
[13] Thorsten Joachims,et al. Making large-scale support vector machine learning practical , 1999 .
[14] Harris Drucker,et al. Support vector machines for spam categorization , 1999, IEEE Trans. Neural Networks.
[15] F ChenStanley,et al. An Empirical Study of Smoothing Techniques for Language Modeling , 1996, ACL.
[16] Jason D. M. Rennie,et al. Improving Multiclass Text Classification with the Support Vector Machine , 2001 .
[17] Michael I. Jordan,et al. On Discriminative vs. Generative Classifiers: A comparison of logistic regression and naive Bayes , 2001, NIPS.
[18] W O Johnson,et al. Screening without a "gold standard": the Hui-Walter paradigm revisited. , 2001, American journal of epidemiology.
[19] Andreas Stolcke,et al. SRILM - an extensible language modeling toolkit , 2002, INTERSPEECH.
[20] Fabrizio Sebastiani,et al. Machine learning in automated text categorization , 2001, CSUR.
[21] Marco Saerens,et al. Adjusting the Outputs of a Classifier to New a Priori Probabilities: A Simple Procedure , 2002, Neural Computation.
[22] Shlomo Argamon,et al. Automatically Categorizing Written Texts by Author Gender , 2002, Lit. Linguistic Comput..
[23] Geoffrey Leech,et al. Grammatical word class variation within the British National Corpus sampler , 2002 .
[24] James J. Lindsay,et al. Cues to deception. , 2003, Psychological bulletin.
[25] J. Pennebaker,et al. Lying Words: Predicting Deception from Linguistic Styles , 2003, Personality & social psychology bulletin.
[26] Dale Schuurmans,et al. Language independent authorship attribution using character level language models , 2003, Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - EACL '03.
[27] Dan Klein,et al. Accurate Unlexicalized Parsing , 2003, ACL.
[28] J. Pennebaker,et al. Psychological aspects of natural language. use: our words, our selves. , 2003, Annual review of psychology.
[29] Dale Schuurmans,et al. Combining Naive Bayes and n-Gram Language Models for Text Classification , 2003, ECIR.
[30] Jeffrey T. Hancock,et al. Deception and design: the impact of communication technology on lying behavior , 2004, CHI.
[31] Dwayne D. Gremler,et al. Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? , 2004 .
[32] Ryan M. Rifkin,et al. In Defense of One-Vs-All Classification , 2004, J. Mach. Learn. Res..
[33] Hector Garcia-Molina,et al. Combating Web Spam with TrustRank , 2004, VLDB.
[34] Jay F. Nunamaker,et al. A Comparison of Classification Methods for Predicting Deception in Computer-Mediated Communication , 2004, J. Manag. Inf. Syst..
[35] R. Rigby,et al. Generalized additive models for location, scale and shape , 2005 .
[36] Moshe Koppel,et al. Determining an author's native language by mining a text for errors , 2005, KDD '05.
[37] Gilad Mishne,et al. Blocking Blog Spam with Language Model Disagreement , 2005, AIRWeb.
[38] Richard Simon,et al. Bias in error estimation when using cross-validation for model selection , 2006, BMC Bioinformatics.
[39] Rich Caruana,et al. Predicting good probabilities with supervised learning , 2005, ICML.
[40] Marcia K. Johnson,et al. Reality Monitoring , 2005 .
[41] Soo-Min Kim,et al. Automatically Assessing Review Helpfulness , 2006, EMNLP.
[42] B. Depaulo,et al. Accuracy of Deception Judgments , 2006, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.
[43] Yee Whye Teh,et al. A Hierarchical Bayesian Language Model Based On Pitman-Yor Processes , 2006, ACL.
[44] Luca Becchetti,et al. A reference collection for web spam , 2006, SIGF.
[45] Marc Najork,et al. Detecting spam web pages through content analysis , 2006, WWW '06.
[46] Jeffrey T. Hancock,et al. On Lying and Being Lied To: A Linguistic Analysis of Deception in Computer-Mediated Communication , 2007 .
[47] A. Vrij,et al. Cues to Deception and Ability to Detect Lies as a Function of Police Interview Styles , 2007, Law and human behavior.
[48] Cindy K. Chung,et al. The development and psychometric properties of LIWC2007 , 2007 .
[49] Max Mühlhäuser,et al. Automatically Assessing the Post Quality in Online Discussions on Software , 2007, ACL.
[50] Marilyn A. Walker,et al. Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text , 2007, J. Artif. Intell. Res..
[51] Lillian Lee,et al. Opinion Mining and Sentiment Analysis , 2008, Found. Trends Inf. Retr..
[52] Douglas Aberdeen,et al. The War Against Spam: A report from the front line , 2007 .
[53] A. Vrij. Detecting Lies and Deceit: Pitfalls and Opportunities , 2008 .
[54] Bing Liu,et al. Opinion spam and analysis , 2008, WSDM '08.
[55] Ling Liu,et al. Do online reviews affect product sales? The role of reviewer characteristics and temporal effects , 2008, Inf. Technol. Manag..
[56] M. de Rijke,et al. Credibility Improves Topical Blog Post Retrieval , 2008, ACL.
[57] Dongsong Zhang,et al. A Statistical Language Modeling Approach to Online Deception Detection , 2008, IEEE Transactions on Knowledge and Data Engineering.
[58] Barry Smyth,et al. Learning to recommend helpful hotel reviews , 2009, RecSys '09.
[59] Carlo Strapparava,et al. The Lie Detector: Explorations in the Automatic Recognition of Deceptive Language , 2009, ACL.
[60] Kyung Hyan Yoo,et al. Comparison of Deceptive and Truthful Travel Reviews , 2009, ENTER.
[61] Jon M. Kleinberg,et al. WWW 2009 MADRID! Track: Data Mining / Session: Opinions How Opinions are Received by Online Communities: A Case Study on Amazon.com Helpfulness Votes , 2022 .
[62] A. Vrij,et al. Outsmarting the Liars: The Benefit of Asking Unanticipated Questions , 2009, Law and human behavior.
[63] Filippo Menczer,et al. Modeling Statistical Properties of Written Text , 2009, PloS one.
[64] Cheol Park,et al. Information direction, website reputation and eWOM effect: A moderating role of product type , 2009 .
[65] Erik Qualman. Socialnomics: How Social Media Transforms the Way We Live and Do Business , 2009 .
[66] Mira Lee,et al. Effects of Valence and Extremity of eWOM on Attitude toward the Brand and Website , 2009 .
[67] Eric Gilbert,et al. Widespread Worry and the Stock Market , 2010, ICWSM.
[68] Jeremy P. Birnholtz,et al. "on my way": deceptive texting and interpersonal awareness narratives , 2010, CSCW '10.
[69] J. Pete Blair,et al. (In)accuracy at Detecting True and False Confessions and Denials: An Initial Test of a Projected Motive Model of Veracity Judgments , 2010 .
[70] Barbara Poblete,et al. Twitter under crisis: can we trust what we RT? , 2010, SOMA '10.
[71] Eni Mustafaraj,et al. From Obscurity to Prominence in Minutes: Political Speech and Real-Time Search , 2010 .
[72] Adriana Kovashka,et al. Authorship Attribution Using Probabilistic Context-Free Grammars , 2010, ACL.
[73] Bill Tomlinson,et al. Who are the crowdworkers?: shifting demographics in mechanical turk , 2010, CHI Extended Abstracts.
[74] Andrew Olney,et al. An Exploration of Off Topic Conversation , 2010, NAACL.
[75] Derek Greene,et al. Merging multiple criteria to identify suspicious reviews , 2010, RecSys '10.
[76] Isabell M. Welpe,et al. Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment , 2010, ICWSM.
[77] Brendan T. O'Connor,et al. From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series , 2010, ICWSM.
[78] Rada Mihalcea,et al. Amazon Mechanical Turk for Subjectivity Word Sense Disambiguation , 2010, Mturk@HLT-NAACL.
[79] Brendan T. O'Connor,et al. A Latent Variable Model for Geographic Lexical Variation , 2010, EMNLP.
[80] T. Levine,et al. Content in Context Improves Deception Detection Accuracy , 2010 .
[81] Bernardo A. Huberman,et al. Predicting the Future with Social Media , 2010, Web Intelligence.
[82] Derek Greene,et al. Distortion as a validation criterion in the identification of suspicious reviews , 2010, SOMA '10.
[83] George Forman,et al. Apples-to-apples in cross-validation studies: pitfalls in classifier performance measurement , 2010, SKDD.
[84] David Yarowsky,et al. Classifying latent user attributes in twitter , 2010, SMUC '10.
[85] Ee-Peng Lim,et al. Detecting product review spammers using rating behaviors , 2010, CIKM.
[86] Arjun Mukherjee,et al. Improving Gender Classification of Blog Authors , 2010, EMNLP.
[87] Qiang Yang,et al. A Survey on Transfer Learning , 2010, IEEE Transactions on Knowledge and Data Engineering.
[88] Panagiotis G. Ipeirotis. Demographics of Mechanical Turk , 2010 .
[89] Aron Culotta,et al. Towards detecting influenza epidemics by analyzing Twitter messages , 2010, SOMA '10.
[90] X. Zhang,et al. Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and Consumer Characteristics , 2010 .
[91] Ana-Maria Popescu,et al. A Machine Learning Approach to Twitter User Classification , 2011, ICWSM.
[92] Carolyn Penstein Rosé,et al. Author Age Prediction from Text using Linear Regression , 2011, LaTeCH@ACL.
[93] Eric P. Xing,et al. Sparse Additive Generative Models of Text , 2011, ICML.
[94] Claire Cardie,et al. Multi-aspect Sentiment Analysis with Topic Models , 2011, 2011 IEEE 11th International Conference on Data Mining Workshops.
[95] Barbara Poblete,et al. Information credibility on twitter , 2011, WWW.
[96] Yejin Choi,et al. Domain Independent Authorship Attribution without Domain Adaptation , 2011, RANLP.
[97] Yejin Choi,et al. Gender Attribution: Tracing Stylometric Evidence Beyond Topic and Genre , 2011, CoNLL.
[98] Jacob Ratkiewicz,et al. Detecting and Tracking Political Abuse in Social Media , 2011, ICWSM.
[99] John D. Burger,et al. Discriminating Gender on Twitter , 2011, EMNLP.
[100] Jacob Ratkiewicz,et al. Predicting the Political Alignment of Twitter Users , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.
[101] Eric P. Xing,et al. Discovering Sociolinguistic Associations with Structured Sparsity , 2011, ACL.
[102] Dragomir R. Radev,et al. Rumor has it: Identifying Misinformation in Microblogs , 2011, EMNLP.
[103] Claire Cardie,et al. Finding Deceptive Opinion Spam by Any Stretch of the Imagination , 2011, ACL.
[104] Yi Yang,et al. Learning to Identify Review Spam , 2011, IJCAI.
[105] Johan Bollen,et al. Twitter mood predicts the stock market , 2010, J. Comput. Sci..
[106] Mark Dredze,et al. You Are What You Tweet: Analyzing Twitter for Public Health , 2011, ICWSM.
[107] Yejin Choi,et al. Distributional Footprints of Deceptive Product Reviews , 2012, ICWSM.
[108] Jeffrey T. Hancock,et al. What Lies Beneath: The Linguistic Traces of Deception in Online Dating Profiles , 2012 .
[109] Subhash C. Kak,et al. A Survey of Prediction Using Social Media , 2012, ArXiv.
[110] Julia Hirschberg,et al. Detecting Hate Speech on the World Wide Web , 2012 .
[111] Beng Soo Ong,et al. The Perceived Influence of User Reviews in the Hospitality Industry , 2012 .
[112] Michael L. Anderson,et al. Learning from the Crowd: Regression Discontinuity Estimates of the Effects of an Online Review Database , 2012 .
[113] Claire Cardie,et al. Estimating the prevalence of deception in online review communities , 2012, WWW.
[114] Alexander J. Smola,et al. Discovering geographical topics in the twitter stream , 2012, WWW.
[115] Arjun Mukherjee,et al. Spotting fake reviewer groups in consumer reviews , 2012, WWW.
[116] Mung Chiang,et al. Why watching movie tweets won't tell the whole story? , 2012, WOSN '12.
[117] Munmun De Choudhury,et al. Not All Moods Are Created Equal! Exploring Human Emotional States in Social Media , 2012, ICWSM.
[118] Aristides Gionis,et al. Correlating financial time series with micro-blogging activity , 2012, WSDM '12.
[119] Yejin Choi,et al. Characterizing Stylistic Elements in Syntactic Structure , 2012, EMNLP.
[120] Dina Mayzlin,et al. Promotional Reviews: An Empirical Investigation of Online Review Manipulation , 2012 .
[121] Scott Counts,et al. Tweeting is believing?: understanding microblog credibility perceptions , 2012, CSCW.
[122] Daniel Gayo-Avello,et al. "I Wanted to Predict Elections with Twitter and all I got was this Lousy Paper" - A Balanced Survey on Election Prediction using Twitter Data , 2012, ArXiv.
[123] Carolyn Penstein Rosé,et al. Detecting offensive tweets via topical feature discovery over a large scale twitter corpus , 2012, CIKM.
[124] Yejin Choi,et al. Syntactic Stylometry for Deception Detection , 2012, ACL.
[125] Adam J. Berinsky,et al. Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk , 2012, Political Analysis.
[126] Claire Cardie,et al. Negative Deceptive Opinion Spam , 2013, NAACL.
[127] Matthias Hagen,et al. Overview of the 1st international competition on plagiarism detection , 2009 .
[128] J. Burgoon,et al. Interpersonal Deception Theory , 2015 .