Do reviewers’ words affect predicting their helpfulness ratings? Locating helpful reviewers by linguistics styles

Information & Management - Tập 56 Số 1 - Trang 28-38 - 2019
Sheng-Tun Li1,2,3, Thuong-Thi Pham3, Hui-Chi Chuang3
1Center for Innovative FinTech Business Models, National Cheng Kung University, No.01 Da-Hsueh Road, East Area, Tainan City, 701, Taiwan
2Department of Industrial and Information Management, National Cheng Kung University, No.01 Da-Hsueh Road, East Area, Tainan City, 701, Taiwan
3Institute of Information Management, National Cheng Kung University, No.01 Da-Hsueh Road, East Area, Tainan City, 701, Taiwan

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Tài liệu tham khảo

Ku, 2012, To whom should I listen? Finding reputable reviewers in opinion-sharing communities, Decis. Supp. Syst., 53, 534, 10.1016/j.dss.2012.03.003

Entwistle, 2003, Relevance, reliability, and the earnings quality debate, Issues Account. Educ., 18, 79, 10.2308/iace.2003.18.1.79

Pennebaker, 1999, Linguisticts style: language use as individual difference, Person. Soc. Psychol., 77, 10.1037/0022-3514.77.6.1296

Hu, 2016, Predicting hotel review helpfulness: the impact of review visibility, and interaction between hotel stars and review ratings, Int. J. Inf. Manage., 36, 929, 10.1016/j.ijinfomgt.2016.06.003

Mudambi, 2010, What makes a helpful online review? A study of customer reviews on amazon.com, MIS Q., 34, 185, 10.2307/20721420

Forman, 2008, Examining the relationship between reviews and sales: the role of reviewer identity disclosure in electronic markets, Inf. Syst. Res., 19, 291, 10.1287/isre.1080.0193

Lee, 2011, Helpful reviewers in TripAdvisor, an online travel community, Jo. Travel Tour. Market., 28, 675, 10.1080/10548408.2011.611739

Hart-Davidson, 2010, A method for measuring helpfulness in online peer review, 115

Hsiao, 2012, Predicting the helpfulness of online product reviewers: a data mining approach, PACIS, 134

Lu, 2010, Exploiting social context for review quality prediction, Proceedings of the 19th International Conference on World Wide Web, 10.1145/1772690.1772761

Liu, 2007, Low-quality product review detection in opinion summarization, Proceedings of the Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), 334

Ma, 2009, Trust relationship prediction using online product review data, 47

Patel, 2017, Mining and predicting reviews to micro-reviews and detection of manipulated reviews for E-commerce websites, Int. J. Emerg. Technol. Comput. Sci., 2

Vermeulen, 2009, Tried and tested: the impact of online hotel reviews on consumer consideration, Tour. Manage., 30, 123, 10.1016/j.tourman.2008.04.008

Golbeck, 2005, Semantic Web interaction through trust network recommender systems, Int. Symp. Wearable Comput., 11

Toms, 2004, Measuring user perceptions of web site reputation, Inf. Process. Manage., 40, 291, 10.1016/j.ipm.2003.08.007

Steedman, 2008, On becoming a discipline, Comput. Linguist., 34, 137, 10.1162/coli.2008.34.1.137

Rubin, 2006, Assessing credibility of weblogs, Proceedings of the AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs (CAAW)

Li, 2011, Online persuasion: how the written word drives WOM: Evidence from consumer-generated product reviews, J. Advert. Res., 51, 239, 10.2501/JAR-51-1-239-257

Kim, 2006, Automatically assessing review helpfulness, 423

Zhang, 2006, Utility scoring of product reviews, 51

Dewaele, 2000, Personality and speech production: a pilot study of second language learners, Pers. Individ. Diff., 28, 355, 10.1016/S0191-8869(99)00106-3

Groom, 2002, Words, J. Res. Pers., 36, 615, 10.1016/S0092-6566(02)00512-3

Pennebaker, 2002, Language use and personality during crises: analyses of mayor rudolph giuliani's press conferences, J. Res. Pers., 36, 271, 10.1006/jrpe.2002.2349

Mairesse, 2007, Using linguistic cues for the automatic recognition of personality in conversation and text, J. Artif. Intell. Res., 30, 457, 10.1613/jair.2349

Metzger, 2007, Making sense of credibility on the web: models for evaluating online information and recommendations for future research, J. Am. Soc. Inf. Sci. Technol., 58, 2078, 10.1002/asi.20672

Weerkamp, 2008, Credibility improves topical blog post retrieval, Proceedings of ACL-08: HLT

DuBay, 2004

Ghose, 2011, Estimating the helpfulness and economic impact of product reviews: mining text and reviewer characteristics, IEEE Trans. Knowl. Data Eng., 23, 1498, 10.1109/TKDE.2010.188

Klare, 1963

McLaughlin, 1969, SMOG grading – a new readability formula, J. Read., 22, 639

Liu, 2015, What makes a useful online review? Implication for travel product websites, Tour. Manage., 47, 140, 10.1016/j.tourman.2014.09.020

Korfiatis, 2012, Evaluating content quality and helpfulness of online product reviews: the interplay of review helpfulness vs. review content, Electron. Comm. Res. Appl., 11, 205, 10.1016/j.elerap.2011.10.003

Agnihotri, 2016, Online review helpfulness: role of qualitative factors, Psychol. Market., 33, 1006, 10.1002/mar.20934

Chafe, 1986, Evidentiality in English conversation and academic writing, 261

Su, 2010, Evidentiality for text trustworthiness detection, 10

Jakobson, 1990, Shifters and verbal categories, 386

Palmer, 2001

DeLancey, 2001, The mirative and evidentiality, J. Pragmat., 33, 369, 10.1016/S0378-2166(01)80001-1

Wang, 2017

J.W. Pennebaker, R.J. Booth, M.E. Francis, Linguistic inquiry and word count: LIWC [Computer software], Austin, TX: liwc.net, (2007).

Liang, 2014, Message characteristics in online product reviews and consumer ratings of helpfulness, Southern Commun. J., 79, 468, 10.1080/1041794X.2014.933870

C.-H. Peng, D. Yin, C.-P. Wei, H. Zhang, How and when review length and emotional intensity influence review helpfulness: Empirical evidence from Epinions.com, (2014).

Chiu, 2005, Website quality and customer's behavioural intention: an exploratory study of the role of information asymmetry, Total Qual. Manage. Bus. Excell., 16, 185, 10.1080/14783360500054277

C. Lovelock, Services marketing: people, technology, strategy in: t. edition. (Ed.), New Jersey: Prentice Hall, 2001.

Biber, 2010, Challenging stereotypes about academic writing: complexity elaboration, explicitness, J. Engl. Acad. Purposes, 9, 2, 10.1016/j.jeap.2010.01.001

Moohebat, 2015, Identifying ISI-indexed articles by their lexical usage: a text analysis approach, J. Assoc. Inf. Sci. Technol., 66, 501, 10.1002/asi.23194

Jin, 2010, How to interpret the helpfulness of online product reviews: bridging the needs between customers and designers, 87

Hu, 2008, Do online reviews affect product sales? The role of reviewer characteristics and temporal effects, Inf. Technol. Manage., 9, 201, 10.1007/s10799-008-0041-2

Ngo-Ye, 2014, The influence of reviewer engagement characteristics on online review helpfulness: a text regression model, Decis. Supp. Syst., 61, 47, 10.1016/j.dss.2014.01.011

Levi, 2014, The social aspect of voting for useful reviews, Behavioral-Cultural Modeling, and Prediction, International Conference on Social Computing, 293

Harris, 2007, An investigation of the computer-mediated communication of emotions, J. Appl. Sci. Res., 3, 2081

Griskevicius, 2009, Fear and loving in las vegas: evolution, emotion, and persuasion, J. Market .Res., 46, 384, 10.1509/jmkr.46.3.384

Thelwall, 2010, Sentiment strength detection in short informal text, J. Am. Soc. Inf. Sci. Technol., 61, 2544, 10.1002/asi.21416

Garcia, 2011, Emotions in product reviews-empirics and models in: privacy, security, risk and trust (PASSAT), 2011 IEEE Third Inernational Conference on Social Computing (SocialCom), 483

Flesch, 1948, A new readability yardstick, J. Appl. Psychol., 32, 221, 10.1037/h0057532

V.N. Vapnik, Statistical learning theory, in: W. New York (Ed.), (1998).

Li, 2015, A regularized monotonic fuzzy support vector machine model for data mining with prior knowledge, IEEE Trans. Fuzzy Syst., 23, 1713, 10.1109/TFUZZ.2014.2374214

C.J. Lin, C.C. Chang, LIBSVM – A library for support vector machines, https://www.csie.ntu.edu.tw/∼cjlin/libsvm/. (2014).

Fast, 2008, Personality as manifest in word use: correlations with self-report, acquaintance report, and behavior, J. Pers. Soc. Psychol., 94, 334, 10.1037/0022-3514.94.2.334

Xia, 2009, You are what you write-Understanding user online behavior through text mining

Jurafsky, 2009

Bei, 2004, Consumers' online information search behavior and the phenomenon of search vs. experience products, J. Fam. Econ. Issues, 25, 449

Beukeboom, 2012, The language of extraversion: extraverted people talk more abstractly, introverts are more concrete, J. Lang. Soc. Psychol.

Nelson, 1970, Information and consumer behavior, J. Polit. Econ., 78, 311, 10.1086/259630

Zeithaml, 1988, Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence, J. Market., 52, 2, 10.1177/002224298805200302