市場(Market)為在某個時間、地點，供給者及消費者將商品及物品進行交換進而達到彼此需求的地方，「行銷」(Marketing) 則為重要的商務活動之一，其任務在了解市場與掌握市場，並施予適當之因應策略，而市場區隔分析與趨勢預測為「掌握市場」之首要工作
由於網路世界的快速發展，許多消費者會在社群媒體上發表自己對於商品的意見及訴求，且消費者會搜尋網路以了解商品內容及其他使用者對於商品的評價，進而影響消費者的購買動機。針對社群媒體內容，分析市場區隔現狀與預測變化趨勢，以提早因應、創造更大的利益與價值，為行銷可行且必要的方向。
基於市場區隔分析之需求性以及社群媒體內容的有效性，本研究提出一社群分析為基之市場區隔分析方法，以供企業了解市場區隔以及其商品於公司所定位之區隔中的優劣，讓企業更有效的改善、創新商品。針對上述目的，本研究主要研究項目包括: (1)商品口碑模型設計， (2)市場區隔方法設計，(3)商品口碑樣貌分析方法設計，(4)市場區隔分析方法實作與驗證。

Market is a place where suppliers and consumers exchange commodities and goods to meet each other's needs at a certain time and place, and marketing is a concept applied to the market. Understand the market segmentation, target market, market positioning and 4P (Product, Promotion, Price, Place) marketing strategy to master the market and propose the most appropriate decision, which is the core method of current marketing.

Due to the rapid development of the internet world, many consumers will express their opinions and demands on products on social media, and consumers will search the Internet to understand the contents of the commodity and other users' evaluation of the commodity, which will affect consumers purchase motivation. However, in recent years, the research has only conducted market analysis on changes in the overall market, but market segmentation analysis can better understand the needs of its own consumers and the product appearance of other companies in the same segment, and find out the advantages and disadvantages of the company and its competitors, then put forward effective strategies.

The main purpose of this research is to use commodity articles and evaluations on social media to construct a market segmentation analysis mechanism to help companies recognize the merits of their commodities and allow them to more effectively improve, innovate, and design commodities. For the above purposes, the main research items of this study include: (1) commodity e-wom model design, (2) market segmentation method design, (3)commodity e-wom profile design, (4) social media-based market analysis method Implementation and verification.

英文部分：
[1] P. Kotler, L. Keller, “Marketing Management 15th edition,” Pearson, 2016.
[2] E. J. McCarthy,“Basic Marketing: a Managerial Approach,” Homewood, IL: Irwin Inc, 1960.
[3] M. Wedel, W. A. Kamakura, “Market segmentation: Conceptual and methodological foundations,” Springer Science & Business Media, Vol.8, 2012.
[4] A. Alamsyah, “Social network data analytics for market segmentation in Indonesian telecommunications industry,” In 2017 5th International Conference on Information and Communication Technology (ICoIC7), pp.1-5, IEEE, 2017.
[5] S. Peker, A. Kocyigit, P. E. Eren, “LRFMP model for customer segmentation in the grocery retail industry: A case study,” Marketing Intelligence & Planning, 35(4), pp.544–559, 2017.
[6] P. Anitha, M. M. Patil, “RFM model for Customer Purchase Behavior using K-Means Algorithm,” Journal of King Saud University-Computer and Information Sciences, In Press, 2019.
[7] Rhegie Nastiti Ayungga1, “Customer Benchmarking Analysis on Brand Image Formation in Brand Nike,” Sinergi : Jurnal Ilmiah Ilmu Manajemen, Vol.8(2), 2018.
[8] D. J. Lim, T. R. Anderson,“Time Series Benchmarking Analysis for New Product Scheduling,” Wiley Online Library, 2017. https://doi.org/10.1002/9781118946688.ch28.
[9] J. Jin, P. Ji, S. Yan, “Comparison of series products from customer online concerns for competitive intelligence,” Journal of Ambient Intelligence and Humanized Computing, Vol.10(3), pp.937-952, 2019.
[10] J. Jin, P. Ji, R. Gu,“Identifying comparative customer requirements from product online reviews for competitor analysis,” Engineering Applications of Artificial Intelligence, Vol.49, pp.61–73, 2016.
[11] P. Lacourbe, C.H. Loch, S. Kavadias, “Product positioning in a two-dimensional market space,” Prod. Oper. Manag., 18(3), pp.315-332, 2009.
[12] W. Qi, X. Luo, H. Wang, X. Liu, Y. Yu, Z. Zhang, "Robust Product Positioning Considering Customer Preferences," in IEEE Systems Journal, vol.13, no.3, pp.2154-2165, 2019.
[13] A. Mehra, S. Sajeesh, S. Voleti, “Impact of Reference Prices on Product Positioning and Profits,” Production and Operations Management, 2019. Available at SSRN: https://ssrn.com/abstract=2847563
[14] SocialMediaToday, https://www.socialmediatoday.com/news/how-much-data-is-generated-every-minute-infographic-1/525692/, 2018.
[15] GSMARENA, https://www.gsmarena.com/, 2021.
[16] I. Mendonça, A. Trouvé, A. Fukuda, K. Murakami, "On clustering algorithms: applications in Word-Embedding documents," Journal of Computers, vol.14, no.2, pp.88-92, 2019.
[17] C. F. Tsai, Y. C. Chen, "The optimal combination of feature selection and data discretization: An empirical study," Inf. Sci., vol.505, pp.282-293, 2019.
[18] T. Hou, B. Yannou, Y. Leroy, E. Poirson, "Mining customer product reviews for product development: A summarization process," Expert Syst. Appl., vol.132, pp.141-150, 2019.
[19] S. Tuarob, C.S. Tucker,“Quantifying product favorability and extracting notable product features using large scale social media data,”Journal of Computing and Information Science in Engineering, 15(3) , pp.031003, 2015.
[20] T. Nguyen Thi Ngoc, H. Nguyen Thi Thu, V. Anh Nguyen, “Mining aspects of customer's review on the social network,” J. Big Data, 6(1), pp.22, 2019.
[21] Z. Yan, M. Xing, D. Zhang, B. Ma, “Exprs: An extended pagerank method for product feature extraction from online consumer reviews,” Inf. Manag., 52(7), pp.850–858, 2015.
[22] K. Ravi, V. Ravi, “A survey on opinion mining and sentiment analysis: tasks, approaches and applications,” Knowledge-Based Systems, 89, pp.14-46, 2015.
[23] P. Kotler, “Marketing Management: Analysis, Planning, Implementation and Control,”9th edition. Englewood Cliffs, N. J.: Prentice-Hall, 1988.
[24] A.C. Tynan, J. Drayton,“Market segmentation,”Journal of marketing management, No.3, pp.301-335, 1987.
[25] J. O. Kim, S. Forsythe, Q. Gu, S. J. Moon,“Cross-cultural Consumer Values, Needs and Purchase Behavior,” Journal of Consumer Marketing, Vol.19, No.6, pp.481-502, 2002.
[26] M. B. Holbrook,“Ethics in consumer research: An Overview and prospectus,” Advances in consumer Research, 21, pp.566-571, 1994.
[27] M. B. Holbrook,“Consumer Value: A Framework for Analysis and Research,” Routledge, New York, pp.1-28, 1999.
[28] M. B. Holbrook, “Customer value and auto ethnography: Subjective personal introspection and the meanings of a photograph collection,” Journal of Business Research, 58(1), pp.45-61, 2005.
[29] J. N. Sheth, B. I. Newman, B. L. Gross, “Why we buy what we buy: a theory of consumption values,”Journal of Business Research, 22, pp.159-170, 1991.
[30] J. N. Sheth, B. I. Newman, B. L. Gross, “Consumption values and market choices: theory and applications,” SouthWestern Publishing, Cincinnati, 1991.
[31] J. S. Mazid, “An Examination of Two Dimensions of Customer Perceived Value in Banking Services,” Journal of Basic and Applied Scientific Research, 2(11), pp.11341-11345, 2012.
[32] D. Keltner, A. M. Kring, “Emotion, Social Function, and Psychopathology,” Review of General Psychology, 2, pp.320-342, 1998.
[33] E. J. Choi, S. H. Kim, “The Study of the Impact of Perceived Quality and Value of Social Enterprises on Customer Satisfaction and Re-Purchase Intention,” International Journal of Smart Home, 7(1), pp.239-252, 2013.
[34] R. Donovan, J. R. Rossiter, G. Marcoolyn, A. Nesdale, “Store Atmosphere and Purchasing Behavior,” Journal of Retailing, pp.283-294, 1994.
[35] L. McAlister, E. Pessemier, "Variety seeking behavior: An interdisciplinary review," Journal of Consumer research, no.3, pp.311-322, 1982.
[36] M. Pihlström, G. J. Brush, “Comparing the Perceived Value of Information and Entertainment Mobile Services,” Psychology & Marketing, 25(8), pp.732-755, 2008.
[37] R. W. Belk, “Possessions and The Extended Self,” Journal of Consumer Research, 15(Sep), pp.139-168, 1988.
[38] K. R. Prasad,“Big Data Sentiment Analysis Using Distributed Computing Approach,”First International Conference on Artificial Intelligence and Cognitive Computing, pp.689-699, 2018.
[39] S. Tuarob, C.S. Tucker, “A product feature inference model for mining implicit customer preferences within large scale social media networks,” In: ASME 2015 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Boston, Massachusetts, 2015.
[40] K. Zhang, R. Narayanan, A. Choudhary,“Voice of the customers: mining online customer reviews for product feature-based ranking,” in Proceedings of the 3rd conference on Online social networks, pp. 11–11, USENIX Association, 2010.
[41] P. D. Turney, M. L. Littman,“Measuring praise and criticism: inference of semantic orientation from association,” ACM Transactions on Information Systems, 21, pp.315-346, 2003.
[42] D. A. Sautera, F. Eisner, P. Ekman, S. K. Scott, “Cross-cultural recognition of basic emotions through nonverbal emotional vocalizations,” In Proceedings of the National Academy of Sciences, 107(6), 2010.
[43] J. Jin, P. Ji, C. K. Kwong,“What makes consumers unsatisfied with your products: Review analysis at a fine-grained level,” Engineering Applications of Artificial Intelligence, Vol.47, pp.38–48, 2016.
[44] M. A. Nielsen, "Neural Networks and Deep Learning", Determination Press, 2015.
[45] R. Assaurt, S. Eiamkanchanalai, “Consumption Values, Personal Characteristics and Behavioral Intentions in Mobile Shopping Adoption,” Faculty of Economics and Business, University of Zagreb, Trište Journal, 27(1), pp.21-41, 2015.
[46] W. Yi-Chia, A. Z. Vasquez-Parraga,“Fitting Consumer Needs to Perceived Product Value: The Example of Apple versus Samsung Products,” Atlantic Marketing Journal, 5(2), pp.151-166, 2016.
[47] S. I. Wu, H. L. Chang,“The Model of Relationship between the Perceived Values and the Purchase Behaviors toward Innovative Products,” Journal of Management and Strategy, 7(2), pp.31-45, 2016.
[48] N. C. Shil, A. Chowdhury,“Enterprise Agility on Consumption Value: Bringing Satisfaction in New Product,” pp.8-16, Published Online: Nov. 21, 2016.
[49] T. Mikolov, K. Chen, G. Corrado, J. Dean,“Efficient Estimation of Word Representations in Vector Space,”In ICLR Workshop Papers, 2013.
[50] Marginalia, The backpropagation algorithm for Word2Vec, http://www.claudiobellei.com/2018/01/06/backprop-word2vec/, 2018.
[51] N. K. Mubaris, K-Means Clustering in Python, https://mubaris.com/posts/kme ans-clustering/, 2017.
[52] Colah, Understanding LSTM Networks, http://colah.github.io/posts/2015-08-Understanding-LSTMs/, 2015
[53] Y. Huang, S. W. Liu,“An Efficient Model for Text Sentiment Analysis,” In Proceedings of the 2nd International Conference on Algorithms, Computing and Artificial Intelligence pp.479–484, 2019.
[54] Y. J. Yang, H.H. Yuan, Y. L. Wang, “Sentiment analysis method for comment text, ”Journal of Nanjing University of Science and Technology, Vol.43, No.3, pp.280-285, 2019.

中文部分：
[55] iThome, 新聞, https://www.ithome.com.tw/news/132838, 2019.
[56] 中研院平衡語料庫詞類標記集, http://ckipsvr.iis.sinica.edu.tw/papers/category_list.pdf, 1998.
[57] 邱智銘, 研究院語料庫-現代漢語詞類與標記原則, https://linganchor.sinica.edu.tw/data/file/LC040907LC08.pdf, 2003.