Modeling of Electronic Word of Mouth Marketing Based on text mining User comments, A new approach On social commerce
Subject Areas :Elham Ramezani 1 , Ali Rajabzadeh Ghatary 2 * , Vahid Baradaran 3 , Maryam Shoar 4
1 - PhD student, Information Technology Management, Faculty of Management, Islamic Azad University, North Tehran Branch, Tehran, Iran.
2 - Information Technology Management, Faculty of Management and Economics, Tarbiat Modares University, Tehran
3 - Associate Professor, Department of Industrial Engineering, Faculty of Technology and Engineering, Islamic Azad University, North Tehran Branch, Tehran, Iran.
4 - Assistant Professor, Department of Industrial Management, Faculty of Management, Islamic Azad University, North Tehran Branch, Tehran, Iran.
Keywords: : Electronic Word Of Mouth(EWOM), Social Commerce, Customers Online Comments , Text Mining, Brand,
Abstract :
The purpose of this article is to present an Electronic Word of Mouth marketing model in social commerce Based on text mining User comments in sale sites. Due to the new research in this field and using the text mining method of user comments to express the variables of this type of marketing model, this research is a kind of Exploratory Developmental Research. The method used in this research Is combination of qualitative and quantitative. In this regard,by studying previous researches As well as receiving, preprocessing and analyzing 11thousand Customers Online Comments In the case of digital products, Repetitive words with a positive label were selected Then, using Word2vec algorithm The variables of the Electronic Word of Mouth marketing model Were extracted using text mining technique. Fitting the model extracted, based on the comments of experts and users of internet sales sites in Iran with the help of a Questionnaire and analysed with statistical tools of least squares. The statistical sample of the second phase Due to the unlimited statistical population it was estimated according to Cochran's formula 384. In order to review and present the final model from the structural equations approach with SmartPLS software was used. The results show that customer interaction, message quality and Customer mental image will have positive and significant impact on the Platform and channel attractiveness of Electronic word of mouth marketing channel, Finally, these two variables will have a positive and significant impact on the Customer behavior and business brand. This model emphasizes new dimensions of variables of the Electronic Word of Mouth marketing model that can be helpful for business owners and marketers.
ABĂLĂESEI, M., & SANDU, R. M.(2014) ELECTRONIC WORD OF MOUTH: FACTORS THAT INFLUENCE PURCHASE INTENTION
Aladwani, A., (2006). An empirical test of the link between web site quality and forward enterprise integration with web customers. Business process. Manag. J. 12 (2), 178–190.
Ahamad, F. (2019). Impact of word-of-mouth, job attributes and relationship strength on employer attractiveness. Management Research Review.
An, J., Ngo, L. V., Chylinski, M., & Tran, Q. (2019). Customer advocates with a generous heart. Journal of Services Marketing.
Chen, H., Duan, W., & Zhou, W. (2017). The interplay between free sampling and word of mouth in the online software market. Decision Support Systems, 95, 82-90.
Cheung, C. M., & Thadani, D. R. (2012). The impact of electronic word-of-mouthcommunication: a literature analysis and integrative model. Decision SupportSystems, 54(1), 461–470.
Cuiping Chen, Tao (Tony) Gao, (2019). "Sender outcomes of online word-of-mouth transmission", Journal of Consumer Marketing, Vol. 36 Issue: 1, pp.197-205
Doma, S. S., Elaref, N. A., & Elnaga, M. A. (2015). Factors Affecting Electronic Word-of-Mouth on Social Networking Websites in Egypt–An Application of the Technology Acceptance Model. Journal of Internet Social Networking & Virtual Communities, 2015, a1-31.
Gerdt, S. O., Wagner, E., & Schewe, G. (2019). The relationship between sustainability and customer satisfaction in hospitality: An explorative investigation using eWOM as a data source. Tourism Management, 74, 155-172.
Handler, A. (2014). An empirical study of semantic similarity in WordNet and Word2Vec.
Hwang, K., & Zhang, Q. (2018). Influence of parasocial relationship between digital celebrities and their followers on followers’ purchase and electronic word-of-mouth intentions, and persuasion knowledge. Computers in Human Behavior, 87, 155-173.
Hussain, S., Guangju, W., Jafar, R. M. S., Ilyas, Z., Mustafa, G., & Jianzhou, Y. (2018). Consumers' online information adoption behavior: Motives and antecedents of electronic word of mouth communications. Computers in Human Behavior, 80, 22-32
Jason Q. Zh. Georgiana C. Dongwoo Sh. (2010). When does electronic word-of-mouth matter? A study of consumer product reviews. Journal of Business Research, 63, 1336–1341.
Kim, H., Ko, E., & Kim, J. (2015). SNS users' para-social relationships with celebrities: Social media effects on purchase intentions. Journal of Global Scholars of Marketing Science, 25(3), 279–294.
Kline, R. B. (2011). Principles and practice of structural equation modeling. London.
Loureiro, S. M., Cavallero, L., & Miranda, F. J. (2018). Fashion brands on retail websites: Customer performance expectancy and e-word-of-mouth. Journal of Retailing and Consumer Services, 41, 131-141.
Mikolov, T., Sutskever, I., Chen, K., Corrado, G. S., & Dean, J. (2013). Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems (pp. 3111-3119).
Le, T. D., Dobele, A. R., & Robinson, L. J. (2018). WOM source characteristics and message quality: the receiver perspective. Marketing Intelligence & Planning, 36(4), 440-454
Sundermann, L. M. (2018). Share experiences: receiving word of mouth and its effect on relationships with donors. Journal of Services Marketing.
Lim, L. M. J. (2016). Analyzing the impact of electronic word of mouth on purchase intention and willingness to pay for tourism related products. Asia Pacific Business & Economics Perspectives, 4(1), 22-50.
Lerrthaitrakul, W., & Panjakajornsak, V. (2014). The impact of electronic word-of-mouth factors on consumers' buying decision-making processes in the low cost carriers: a conceptual framework. International Journal of Trade, Economics and Finance, 5(2), 142.
Lin, C., Wu, Y. S., & Chen, J. C. V. (2013). Electronic word-of-mouth: The moderating roles of product involvement and brand image. TIIM 2013 Proceedings, 39-47.
Martínez-Torres, M. R., Arenas-Marquez, F. J., Olmedilla, M., & Toral, S. L. (2018). Identifying the features of reputable users in eWOM communities by using Particle Swarm Optimization. Technological Forecasting and Social Change, 133, 220-228.
Mahapatra, S. and Mishra, A. (2017), “Acceptance and forwarding of electronic word of mouth”,Marketing Intelligence & Planning, Vol. 35 No. 5, pp. 594-610.
Matzler, K., Teichmann, K., Strobl, A., & Partel, M. (2019). The effect of price on word of mouth: First time versus heavy repeat visitors. Tourism Management, 70, 453-459.
Nuseir, M. T. (2019). The impact of electronic word of mouth (e-WOM) on the online purchase intention of consumers in the Islamic countries–a case of (UAE). Journal of Islamic Marketing.
Pandey, S., Chawla, D.,( 2016). Understanding indian online clothing shopper loyalty and disloyalty: the impact of E-lifestyles and website quality. J. Internet Commer. 15 (4), 332–352.
Previte, J., Russell-Bennett, R., Mulcahy, R., & Hartel, C. (2019). The role of emotional value for reading and giving eWOM in altruistic services. Journal of Business Research, 99, 157-166.
Rahman, M. S., & Mannan, M. (2018). Consumer online purchase behavior of local fashion clothing brands. Journal of Fashion Marketing and Management: An International Journal.
Shan, Y., (2016). How credible are online product reviews? The effects of self-generated and system-generated cues on source credibility evaluation. Comput. Hum. Behav. 55, 633–641.
Shah, S.S.H., Aziz, J., Jaffari, A.R., Waris, S., Ejaz, W., Fatima, M. and Sherazi, S.K. (2012), “The impact of brands on consumer purchase intentions”, Asian Journal of Business Management, Vol. 4No. 2, pp. 105-110.
Shaikh, A. A., Karjaluoto, H., & Häkkinen, J. (2018). Understanding moderating effects in increasing share-of-wallet and word-of-mouth: A case study of Lidl grocery retailer. Journal of Retailing and Consumer Services, 44, 45-53.
Teso, E., Olmedilla, M., Martínez-Torres, M. R., & Toral, S. L. (2018). Application of text mining techniques to the analysis of discourse in eWOM communications from a gender perspective. Technological Forecasting and Social Change, 129, 131-142.
Tien, D. H., Rivas, A. A. A., & Liao, Y. K. (2019). Examining the influence of customer-to customer electronic word- of-mouth on purchase intention in social networking sites. Asia Pacific Management Review, 24(3), 238-249.
Vásquez, C., (2015). The Discourse of Online Consumer Reviews, Bloomsbury. Walther, J.B., (1992). Interpersonal effects in computer-mediated interaction. A relational perspective. Commun. Res. 19 (1), 52–90.
Wang, Z., Li, H., Ye, Q., & Law, R. (2016). Saliency effects of online reviews embedded in the description on sales: Moderating role of reputation. Decision Support Systems, 87, 50-58.
Wen-Hai, C., Yuan, C. Y., Liu, M. T., & Fang, J. F. (2018). The effects of outward and inward negative emotions on consumers’ desire for revenge and negative word of mouth. Online Information Review.
Wetzels, M., Odekerken-Schröder, G., & Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 177-195.
Zainuddin, N., Previte, J., & Russell-Bennett, R. (2011). A social marketing approach to value creation in a well-women's health service. Journal of Marketing Management, 27, 361–385.