참고문헌
- H. J. Jang. (2017. 3. 31). Worldwide attention, Steam 1st battle ground, Game performance is the most important. THIS IS GAME. http://www.thisisgame.com/webzine/news/nboard/5/?n=70753
- S. Y. Park. (2015. 2. 27). Steam, active account exceeded 125 million, ZD NET Korea. http://www.zdnet.co.kr/news/news_view.asp?artice_id=20150227091302.
- Christiansen. T & S. S. Tax. (2000). Measuring Word of Mouth: The Questions of Who and When. Journal of Marketing Communications, 6(3), 185-199. https://doi.org/10.1080/13527260050118676
- Goh, J. M., G. G. Gao. & R. Agarwal. (2016). The creation of social value: Can an online health community reduce rural-urban health disparities?. Management Information Systems Quarterly, 40(1), 247-263. https://doi.org/10.25300/MISQ/2016/40.1.11
- S. R. Back. (2005). An exploratory study of motives toward word of mouth activities on the Internet. The Korean Journal of Advertising and Public Relations, 7(1), 108-144.
- Zhang. W. & S. Watts. (2003). Knowlege Adoption in Online Communities of Practice. International Conference on Information Systems, Atlanta, AIS, 35(3), 96-109.
- Henning-Thurau. T., K. P. Gwinner., G. Walsh. & D. D. Gremler. (2004). Electronic Word-of-Mouth via Consumer-Opinion Platforms: What Motives Consumers to Articulate Themselves on the Internet?. Journal of Interactive Marketing, 18(1), 32-52. https://doi.org/10.1002/dir.20004
- Chatterjee. P. (2001). Online Review - Do Consumers Use Them?. Advances in Consumer Research, 28, 129-133.
- Mcknight. H. D., V. Choudhury., & C. Kacmar. (2002). Developing and Validating Trust Measures for e-Commerce: An Integrative Typology. Information Systems Research, 13(3), 334-359. https://doi.org/10.1287/isre.13.3.334.81
- Brown. J. J., A. J. Broderick., & N. Lee. (2007). Word of Mouth Communication with Online Communication : Conceptualizing the Online Social Network. Journal of Interactive Marketing, 21(3), 2-20. https://doi.org/10.1002/dir.20082
- Schindler. R. M. & B. Bickart.(2005, January). Published Word of Mouth: Referable, Consumer-Generated Information on the Internet. In C. P. Haugtvedt, K. A. Machleit and R. F. Yalch(eds.) .(pp. 35-61). Online Consumer Psychology, NJ: Lawrence Erlbaum Associates.
- I. K. Kim. (2016). The dynamics of online word-of-mouth and marketing performance : exploring mobile game application reviews using text-mining and machine-learning. ph.D. dissertation. Korea University, Seoul.
- B. Y. Choi. (2017). Understanding and application of consumer behavior. Seoul : Parkyongsa.
- H. S. Byeon & M. S. Yim. (2014). The Impact of Users' Congruity and Emotion on Intention to Game Use. Journal of Digital Convergence, 12(11), 89-98. https://doi.org/10.14400/JDC.2014.12.11.89
- Y. J. Jo. (2015). A Study on the Influence of Connectivity and Convenience of Smartphones of Word-of mouth Intentions in the Convergence Era : Focused on the Mediating Effects of Application. Journal of Digital Convergence, 13(5), 69-78. https://doi.org/10.14400/JDC.2015.13.5.69
- D. S. Yorm. (2016). Factors Affecting User Satisfaction of Mobile Social Network Games : Focusing on the Quality and Self-determination. Journal of Digital Convergence, 14(11), 459-467. https://doi.org/10.14400/JDC.2016.14.11.459
- D. S. Youm. (2017). The Effect of Perceived Enjoyment and User Characteristics on Intention of Continuous Use of Mobile Social Network Games : Focusing on Mediating Effect of Flow Experience. Journal of Digital Convergence, 15(9), 415-425. https://doi.org/10.14400/JDC.2017.15.9.415
- J. W. Kang. (2008). Game and Culture Research. Seoul : Communication Books.
- S. T. Park., H. C. Lee., T. U. Kim & S. M. Choi. (2012). A Study on Factors Influencing Attachment of Gamers to MMORPG On-line Games. Journal of Digital Convergence, 10(2), 109-119. https://doi.org/10.14400/JDPM.2012.10.2.109
- Dang, Shilpa & Peerzada Hamid Ahmad. (2014). Text Mining: Techniques and its Application. International Journal of Engineering & Technology Innovations, ISSN (Online) : 2348-0866, 1(4), 22-25.
- C. N. Jun. & I. O. Seo. (2013). Analyzing the Bigdata for Practical Using into Technology Marketing : Focusing on the Potential Buyer Extraction. Korean Strategic Marketing Association, 21(2), 181-203.
- Dang, Dr. Shilpa & Peerzada Hamid Ahmad. (2015). A Review of Text Mining Techniques Associated with Various Application Areas. International Journal of Science and Research (IJSR), 4(2), 2461-2466. https://doi.org/10.21275/v4i11.NOV151645
- S. H. Seo & J. T. Kim. (2016). Deep Learning Based Emotion Analysis Research Trend. Korea Multimedia Society, 20(3), 8-22.
- Chen, H. & Zimbra. D. (2010). AI and opinion mining. Intelligent Systems. IEEE, 25(3), 74-80.
- Nasukawa. T. & Yi. J. (2003). Sentimentanalysis: Capturing favorability using natural language processing. In Proceedings of the 2nd international conference on Knowledge capture. (pp. 70-77). ACM.
- O'Connor. B., Balasubramanyan. R., Routledge B. R., & Smith. N. A. (2010). From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. ICWSM, 11, 122-129.
- Hu. M. & Liu. B. (2004). Mining and summarizing customer reviews. KDD'04 Proceedings of the tenth international conference on knowledge discovery and data mining. (pp. 168-177). ACM SIGKDD.
- Esulim. A. & Sebastiani. F. (2006). SentiWordNet: A Publicly Available Lexical Resource for Opinion Mining. Proceedings of LREC. (pp. 417-422). ITALY
- Baccianella. S., Esuli. A. & Sebastiani. F. (2010). SentiWordNet 3.0: An Enganced Lexical Resource for Sentiment Analysis and Opinion Mining. LREC, 10, 2200-2204.
- Liu. S. M & Chen. J. H. (2015). A multi-label classification based approach for sentiment classification. Expert Systems with Applications, 42(3), 1083-1093. https://doi.org/10.1016/j.eswa.2014.08.036
- Arcjak. N., A. Ghose & P. G. Ipeirotis. (2007). Show me the money!. Proceedings on the 13th International Conference. (pp. 56-65). ACM SIGKDD.
- Archak. N., A. Ghose, & P. G. Ipeirotis. (2011). Deriving the Pricing Power of Product Features by Mining Consumer Reviews. Management Science, 57(8), 1485-1509. https://doi.org/10.1287/mnsc.1110.1370
- Berger. J., A. T. Sorensen. & S. J. Rasmussen. (2010). Positive Effects of Negative Publicity: When Negative Reviews Increase Sales. Marketing Science, 29(5), 815-827. https://doi.org/10.1287/mksc.1090.0557
- W. J. Chu. & M. J. Roh. (2014). Exploring the Role of Preference Heterogeneity and Causal Attribution in Online Ratings Dynamics. Asia Marketing Journal, 15(4), 61-101.
- J. H. Lee, S. Hong & D. Kang. (2014). The Marketing Success Factors of Hyundai Card Company: Business Model, Development of Goods and BTL Marketing. Korea Business Review, 18(3), 147-170.
- Chintagunta. P. K., S. Gopinath & S. Venkataraman. (2010). The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets. Marketing Science, 29(5), 944-957. https://doi.org/10.1287/mksc.1100.0572
- Dellarocas. C., G. Gao. & R. Narayan. Are Consumers More Likely to Contribute Online Reviews for Hit or Niche Products?. Journal of Management Information Systems. 27(2), 127-157. https://doi.org/10.2753/MIS0742-1222270204
- H. K. Lee & H. Kwak. (2013). Investigation of Factors Affecting the Effects of Online Consumer Reviews. Informatization policy, 20(3), 3-17.
- H. W. Hwangbo & J. H. Kim. (2016). A Study on the Factors Affecting to the Export Performance for Korean Drama Using Sentimental Analysis. The e-Business Studies, 17(6), 87-99. https://doi.org/10.20462/tebs.2016.12.17.6.87
- Y. Liu. (2006). Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue. Journal of Marketing, 70(3), 74-89. https://doi.org/10.1509/jmkg.70.3.74
- Y. K. Kim. (2013). A Study on Relationship between the Relationship Benefit, Customer Satisfaction and Loyalty of Internet Shopping Malls. Daehan Academy of Management Information Systems, 32(4), 155-187.
- Sawhney. M. S. & J. Eliashberg. (1996). A parsimonious model for forecasting gross box-office revenues of motion pictures. Marketing Science, 15(2), 113-131. https://doi.org/10.1287/mksc.15.2.113
- Duan. W., B. Gu. & B. Whinston. (2008). Do online reviews matter?: An empirical investigation of panel data. Decision Support Systems, 45(4), 1007-1016. https://doi.org/10.1016/j.dss.2008.04.001
- Pang. B., Lee. L. & Vaithyanathan. S. (2002). Thumbs up?: sentiment classification using machine learning techniques. In Proceedings of the ACL-02 conference on Empirical methods in natural language processing. (pp. 79-86). ACM.
- Manning. C. D., Raghavan. P. & Schutze. H. (2008). Introduction to Information Retrival. Cambrige: Cambridge university press, 1(1).
- Tay. F. E. & Cao. L. (2001). Application of support vector machines in financial time series forecasting. Omega, 29(4), 309-317. https://doi.org/10.1016/S0305-0483(01)00026-3
- Tong. S. & Koller. D. (2002). Support Vector Machine Active Learning with Applications to Text Classification. The Journal of Machine Learning Research, 2, 45-66.
- Pak. A. & P. Paroubek. (2010). Twitter as a corpus for sentiment analysis and opinion mining. Proceedings of the Seventh International Conference on Language Resources and Evaluation(pp. 1320-1326). Valletta.
- Kumar. A. & Sebastian. T. M. (2012). Sentiment Analysis on Twitter Issue. IJCSI, 9(3), 372-378
- H. J. Kim, K. H. Han & S. S. Shin. (2017). Crepe Search System Design using Web Crawling, Journal of Digital Convergence, 15(11), 261-269. https://doi.org/10.14400/JDC.2017.15.11.261
- Y. Y. Kim & M. Song. (2016). A Study on Analyzing Sentiments on Movie Reviews by Multi-Level Sentiment Classifier, Journal of intelligence and information systems, 22(3), 71-89. https://doi.org/10.13088/jiis.2016.22.3.071
- P. G. Preethi., V. Uma & Ajit kumar. (2015). Temporal Sentiment Analysis and Causal Rules Extraction from Tweets for Event Prediction. Procedia Computer Science, 48, 84-89. https://doi.org/10.1016/j.procs.2015.04.154
- Coovert. M. D. & G. D. Reeder. (1990). Negativity Effects in Impression Formation: The Role of Unit Formation and Schematic Expectations. Journal of Experimental Social Psychology, 26(1), 49-62. https://doi.org/10.1016/0022-1031(90)90061-P
- J. S. Kim, T. Y. Lee, T. G. Kim & H. W. Jung. (2015). Studies on the development scheme and the current state of Korea Game Industry. Journal of Digital Convergence, 13(1), 439-447. https://doi.org/10.14400/JDC.2015.13.1.439