臺灣博碩士論文加值系統

近年來的網路媒體重新定義了消費者與品牌的溝通方式，消費者更傾向於接受非官方的貼文與評論等資訊，各式各樣的論壇便成為能夠獲得消費者最直接的想法與意見的重要平臺。當品牌有任何對消費者有害、反感的事情發生時，人們馬上就會發起討論，且開始於各大論壇留下批評，若品牌不能立即有效的解決問題時，消費者便會自發性地抵制產品、品牌，讓其他消費者會因為其網路評論，而產生了參與抵制行為的心理，抵制行為就消費者角度而言，是讓公司的政策或策略改變的一種方式，但就公司而言，卻是一種不受歡迎的行為，對公司的銷售額和品牌形象會有所傷害，若品牌能夠以特定類型的訊息對消費者做出回應，即時維護住品牌形象，博取消費者好感，或許能在一定程度上遏止消費者的抵制參與及抵制意圖，因此，本研究摸擬線上論壇，欲探討人們在閱讀大量的品牌相關評論後，是否會對消費者的抵制意圖與抵制參與的程度產生影響。本研究根據過往文獻及利用爬蟲抓取文章評論、Jibea斷詞與詞頻分析，結合SnowNLP情感分析套件，並利用問卷調查進行資料收集。本研究亦採用眼動及膚電等儀器來觀察受試者的生理訊號在面對不同品牌的網路評論等操弄時的變化。根據研究結果驗證，抵制意圖對抵制參與有顯著影響力；抵制參與對購買意願有顯著影響力，在觀看網路論壇的環境下，消費者受到情感字眼刺激表現出想要加入討論或尋找抵制目標負面論證的態度將顯著影響抵制參與，網路評論態度影響抵制意圖有顯著影響力；產品印象對抵制意圖有顯著影響力，而眼動行為與抵制參與有關連性，多數受試者在觀看完負向類型評論後，會選擇投入抵制參與行為。

Boycotts are often utilized as one of the most effective consumer actions against companies that engage in practices deemed disgusting, unethical or unjustified. Modern consumers are free to comment about a product or company on the Internet. Negative review comments may influence people who read them. Online review comments have a key role in making purchase decisions, and have effects of persuasion. For instance, people might resist specific products because of negative comments online. Therefore, exploring the relationship between the specified emotions from comments and the boycott intention should help for the companies better understand their customers. Accordingly, this investigation adopts an online crawler tool, Web Scraper, and applies the datamining algorithm SnowNLP which can be employed to analyze natural language and its meaning. The boycott intention has significant influence on boycott participation; boycott participation has significant influence on the purchase intention, boycott intention, and eye movement behavior and resistance participation, most subjects will choose to resist participation after watching negative type comments.
Experimental results also show the physiological signals along with the marketing events. GSR and Eye signals have also indicated participant physical response to the boycott intention. However, this study still has limitations. Finally, this research proposed discussion and management implications for the research results and findings, and help the industry understand its marketing.

摘要..............................................i
Abstract.........................................ii
誌謝............................................iii
目錄.............................................iv
表目錄...........................................vi
圖目錄.........................................viii
第一章 緒論.......................................1
1.1 研究背景與動機................................1
1.2 研究目的......................................2
1.3 研究流程......................................2
第二章 文獻探討...................................4
2.1 抵制(Boycott).................................4
2.1.1 抵制意圖(Boycott Intention).................7
2.1.2 抵制參與(Boycott Participation).............7
2.2 線上評論(Online Review).......................7
2.3 文字探勘(Text Mining).........................8
2.3.1 Web Scraper爬蟲工具.........................9
2.3.2 中文斷詞(Chinese Text Segmentation).........9
2.3.3 情感分析(Sentiment Analysis)................9
2.4 膚電反應......................................9
2.5 眼球追蹤.....................................12
第三章 研究方法..................................16
3.1 研究架構.....................................16
3.1.1 文字情感與抵制意圖.........................16
3.1.2 網路評論態度...............................16
3.1.3 抵制參與及購買意願.........................16
3.1.4 研究架構...................................16
3.2 研究變數.....................................17
3.2.1 問卷構面之操作型定義與問卷設計.............17
3.2.2 前測問卷...................................20
3.2.3 正式問卷之問卷設計.........................20
3.3 文字探勘研究.................................20
3.3.1 數據預處理.................................21
3.3.2 中文斷詞(Segementation)....................21
3.3.3 情感分析...................................21
3.4 生理訊號實驗研究.............................21
3.4.1 研究對象...................................23
3.4.2 實驗環境與設備.............................23
第四章 資料分析..................................26
4.1 前測問卷分析.................................26
4.2 正式問卷分析.................................27
4.2.1 敘述性統計.................................27
4.2.2 測量模式評估...............................29
4.2.3 結構模式評估...............................33
4.3 文字探勘分析.................................34
4.4 生理訊號實驗分析.............................42
4.3.1 膚電實驗分析...............................43
4.3.2 眼動分析...................................52
第五章 討論與結論................................54
5.1 研究意涵.....................................54
5.2 管理意涵.....................................55
5.3 研究限制與建議...............................55
參考文獻.........................................56
附錄一 正式問卷與受試者分組題項..................63
附錄二 實驗畫面..................................67
附錄三 受試者實驗後問項..........................72
附錄四 實驗研究參與同意書........................73
附錄五 結巴與詞頻分析程式碼......................76
Extended Abstract................................78

[1]黃玟瑀. (2015). 影響消費者抵制行為因素之研究.
[2]蔡政旻, 林純純, 洪祺森, and and 蔡旺晉. (2013). 眼球追蹤技術應用於商品喜好評估. 2013ICIMD 創新管理與設計跨領域研討會.
[3]莊雅筑（2012）。運用眼球追蹤法輔助國小六年級學生不同形式科學文本閱讀效益之研究。
[4]陳學志, 賴惠德, and and 邱發忠. (2010). 眼球追蹤技術在學習與教育上的應用. 教育科學研究期刊, 55(4), 39-68.
[5]以眼動儀進行認知歷程-以國立自然科學博物館之拿麼厲害特展為例. 2021. PhD Thesis.
[6]趙玉娟, and and 陶振超. (2018). 政治網路口碑的情感分析: 語意關連性之觀點. 傳播研究與實踐, 8(2), 75-107.
[7]吳肇銘, 金志聿, and and 蔡毓霖. (2019). 運用文字探勘於教學評鑑分析之研究-以中原大學資管系課程為例. 商管科技季刊, 20(4), 437-468.
[8]黃金蘭, Chung, C. K., Hui, N., 林以正, 謝亦泰, Lam, B. C., ... and and Pennebaker, J. W. (2012). 中文版 [語文探索與字詞計算] 詞典之建立. The Development of the Chinese Linguistic Inquiry and Word Count Dictionary. 中華心理學刊, 54(2), 185-201.

[1]Adhami, M. (2013). Using neuromarketing to discover how we really reel about apps. International Journal of Mobile Marketing, 8(1), 95-103.
[2]Aggarwal, P., and Vaidyanathan, R. (2003). Use it or lose it: purchase acceleration effects of time‐limited promotions. Journal of Consumer Behaviour: An International Research Review,2(4), 393-403.
[3]Abdous, M. H., and and He, W. (2011). Using text mining to uncover students' technology‐related problems in live video streaming. British Journal of Educational Technology, 42(1), 40-49.
[4]Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
[5]Ajzen, I., and and Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological bulletin, 82(2), 261.
[6]Amblee, N., and and Bui, T. (2008). Can brand reputation improve the odds of being reviewed on-line?. International Journal of Electronic Commerce, 12(3), 11-28.
[7]Arapakis, I., Lalmas, M., Cambazoglu, B. B., Marcos, M. C., and and Jose, J. M. (2014). User engagement in online N ews: Under the scope of sentiment, interest, affect, and gaze. Journal of the Association for Information Science and Technology, 65(10), 1988-2005.
[8]Auger, P., Burke, P., Devinney, T. M., and and Louviere, J. J. (2003). What will consumers pay for social product features?. Journal of business ethics, 42(3), 281-304.
[9]Bagozzi, R. P., and and Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
[10]Bakker, J., Pechenizkiy, M., and and Sidorova, N. (2011, December). What's your current stress level? Detection of stress patterns from GSR sensor data. In 2011 IEEE 11th international conference on data mining workshops (pp. 573-580). IEEE.
[11]Barakat, A., and and Moussa, F. (2017). Using the expectancy theory framework to explain the motivation to participate in a consumer boycott 1. Journal of Marketing Development and Competitiveness, 11(3), 32-46.
[12]Bhatt, S., Agrali, A., Suri, R., and and Ayaz, H. (2018, July). Does comfort with technology affect use of wealth management platforms? Usability testing with fNIRS and eye-tracking. In International Conference on Applied Human Factors and Ergonomics (pp. 83-90). Springer, Cham.
[13]Boote, J. (1998). Towards a comprehensive taxonomy and model of consumer complaining behaviour. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 11, 140-151.
[14]Borders, A., Earleywine, M., and and Huey, S. (2004). Predicting problem behaviors with multiple expectancies: Expanding expectancy-value theory. Adolescence, 39(155), 539-550.
[15]Bos, J. D., and and Luiten, R. M. (2009). Skin immune system. Skin Cancer after Organ Transplantation, 45-62.
[16]Boucsein, W. (2012). Electrodermal activity. Springer Science and and Business Media.
[17]Brantner, C., Lobinger, K., and and Wetzstein, I. (2011). Effects of visual framing on emotional responses and evaluations of news stories about the Gaza conflict 2009. Journalism and and Mass Communication Quarterly, 88(3), 523-540.
[18]Brigham, F. J., Zaimi, E., Matkins, J. J., Shields, J., McDonnouugh, J., and and Jakubecy, J. J. (2001). The eyes may have it: Reconsidering eye-movement research in human cognition. In Technological Applications. Emerald Group Publishing Limited.
[19]Buswell, G. T. (1935). How people look at pictures: a study of the psychology and perception in art.
[20]Byrne, D. (2005). Social exclusion. McGraw-Hill Education.
[21]Campbell-Sills, L., Barlow, D. H., Brown, T. A., and and Hofmann, S. G. (2006). Acceptability and suppression of negative emotion in anxiety and mood disorders. Emotion, 6(4), 587.
[22]Chen, G., Wan, Y., and and Xu, X. (2016, November). An analysis of the sales and consumer preferences of e-cigarettes based on text mining of online reviews. In 2016 3rd International Conference on Systems and Informatics (ICSAI) (pp. 1045-1049). IEEE.
[23]Chen, P. Y., Wu, S. Y., and and Yoon, J. (2004). The impact of online recommendations and consumer feedback on sales.
[24]Chen, Y., and and Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix. Management science, 54(3), 477-491.
[25]Cheung, C. M., Lee, M. K., and and Rabjohn, N. (2008). The impact of electronic word‐of‐mouth: The adoption of online opinions in online customer communities. Internet research.
[26]Cossío-Silva, F. J., Revilla-Camacho, M. Á., Palacios-Florencio, B., and and Benítez, D. G. (2019). How to face a political boycott: the relevance of entrepreneurs’ awareness. International Entrepreneurship and Management Journal, 15(2), 321-339.
[27]Critchley, H. D. (2002). Electrodermal responses: what happens in the brain. The Neuroscientist, 8(2), 132-142.
[28]Davidson, R. J. (1992). Anterior cerebral asymmetry and the nature of emotion. Brain and cognition, 20(1),125-151.
[29]Dawson, M. E., Schell, A. M., and and Filion, D. L. (2017). The electrodermal system.
[30]de Santos Sierra, A., Ávila, C. S., Casanova, J. G., and and Del Pozo, G. B. (2011). A stress-detection system based on physiological signals and fuzzy logic. IEEE Transactions on Industrial Electronics, 58(10), 4857-4865.
[31]Deans, P., O’Laughlin, L., Brubaker, B., Gay, N., and and Krug, D. (2010). Use of eye movement tracking in the differential diagnosis of attention deficit hyperactivity disorder (ADHD) and reading disability. Psychology, 1(04), 238.
[32]Dellarocas, C. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. Management science, 49(10), 1407-1424.
[33]Ding, X., Liu, B., and and Yu, P. S. (2008, February). A holistic lexicon-based approach to opinion mining. In Proceedings of the 2008 international conference on web search and data mining (pp. 231-240).
[34]Duchowski, A. T. (2002). A breadth-first survey of eye-tracking applications. Behavior Research Methods, Instruments, and and Computers, 34(4), 455-470.
[35]Etzioni, O., Cafarella, M., Downey, D., Popescu, A. M., Shaked, T., Soderland, S., ... and and Yates, A. (2005). Unsupervised named-entity extraction from the web: An experimental study. Artificial intelligence, 165(1), 91-134.
[36]Farah, M. F. (2014). An expectancy-value approach to the study of beliefs underlying consumer boycott intention.
[37]Figner, B., and and Murphy, R. O. (2011). Using skin conductance in judgment and decision making research. A handbook of process tracing methods for decision research, 163-184.
[38]Fornell, C., and and Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics.
[39]Fowles, D. C., Christie, M. J., Edelberg, R., Grings, W. W., Lykken, D. T., and and Venables, P. H. (1981). Publication recommendations for electrodermal measurements. Psychophysiology, 18(3), 232-239.
[40]Friedman, M. (1991). Consumer boycotts: A conceptual framework and research agenda. Journal of Social Issues, 47(1), 149-168.
[41]Gao, B., Liu, T. Y., Qin, T., Zheng, X., Cheng, Q. S., and and Ma, W. Y. (2005, November). Web image clustering by consistent utilization of visual features and surrounding texts. In Proceedings of the 13th annual ACM international conference on Multimedia (pp. 112-121).
[42]Garrett, D. E. (1987). The effectiveness of marketing policy boycotts: Environmental opposition to marketing. Journal of marketing, 51(2), 46-57.
[43]Giannakakis, G., Pediaditis, M., Manousos, D., Kazantzaki, E., Chiarugi, F., Simos, P. G., ... and and Tsiknakis, M. (2017). Stress and anxiety detection using facial cues from videos. Biomedical Signal Processing and Control, 31, 89-101.
[44]Gitlin, T. (2003). The whole world is watching: Mass media in the making and unmaking of the new left. Univ of California Press.
[45]Gobel, M. S., Kim, H. S., and and Richardson, D. C. (2015). The dual function of social gaze. Cognition, 136, 359-364.
[46]Groeppel-Klein, A. (2005). Arousal and consumer in-store behavior. Brain research bulletin, 67(5), 428-437.
[47]Hair Jr, J. F., Sarstedt, M., Ringle, C. M., and and Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. saGe publications.
[48]Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., and and Tatham, R. L. (2006). Multivariate data analysis 6th Edition. Pearson Prentice Hall. New Jersey. humans: Critique and reformulation. Journal of Abnormal Psychology, 87, 49-74.
[49]Henderson, J. M., and and Hollingworth, A. (2003). Eye movements and visual memory: Detecting changes to saccade targets in scenes. Perception and and psychophysics, 65(1), 58-71.
[50]Hennig-Thurau, T., Gwinner, K. P., Walsh, G., and and Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: what motivates consumers to articulate themselves on the internet?. Journal of interactive marketing, 18(1), 38-52.
[51]Hennig-Thurau, T., Walsh, G., and and Walsh, G. (2003). Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the Internet. International journal of electronic commerce, 8(2), 51-74.
[52]Henseler, J., Ringle, C. M., and and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the academy of marketing science, 43(1), 115-135.
[53]Ho, H. F. (2014). The effects of controlling visual attention to handbags for women in online shops: Evidence from eye movements. Computers in Human Behavior, 30, 146-152.
[54]Hoffmann, S., and and Müller, S. (2009). Consumer boycotts due to factory relocation. Journal of Business Research, 62(2), 239-247.
[55]Holper, L., and and Murphy, R. O. (2014). Hemodynamic and affective correlates assessed during performance on the Columbia Card Task (CCT). Brain imaging and behavior, 8(4), 517-530.
[56]Hsu, C. S. (2018). Understanding post-adoption intention of hospitality information system based on Software-as-a-Service (Saas). Advances in Business, Hospitality, and Tourism Research, 1, 335-342.
[57]Hu, L. T., and and Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
[58]Hu, M., and and Liu, B. (2004, July). Mining opinion features in customer reviews. In AAAI (Vol. 4, No. 4, pp. 755-760).
[59]Hung, J. L. (2012). Trends of e‐learning research from 2000 to 2008: Use of text mining and bibliometrics. British journal of educational technology, 43(1), 5-16.
[60]Ingvaldsen, J. E., and and Gulla, J. A. (2012). Industrial application of semantic process mining. Enterprise Information Systems, 6 (2), 139–163. DOI, 10(17517575.2011), 593103.
[61]Jiang, J. T. (2018). A public opinion observer for the social media sphere-Using Facebook news fan pages as an example
[62]Jiménez, F. R., and and Mendoza, N. A. (2013). Too popular to ignore: The influence of online reviews on purchase intentions of search and experience products. Journal of Interactive Marketing, 27(3), 226-235.
[63]John, A., and and Klein, J. (2003). The boycott puzzle: Consumer motivations for purchase sacrifice. Management Science, 49(9), 1196-1209.
[64]Kellough, J. L., Beevers, C. G., Ellis, A. J., and and Wells, T. T. (2008). Time course of selective attention in clinically depressed young adults: An eye tracking study. Behaviour research and therapy, 46(11), 1238-1243.
[65]Kozinets, R. V., and and Handelman, J. (1998). Ensouling consumption: A netnographic exploration of the meaning of boycotting behavior. ACR North American Advances.
[66]Kozinets, R. V., and and Handelman, J. (1998). Ensouling consumption: A netnographic exploration of the meaning of boycotting behavior. ACR North American Advances.
[67]Ku, L. W., Lo, Y. S., and and Chen, H. H. (2007, May). Using polarity scores of words for sentence-level opinion extraction. In Proceedings of NTCIR-6 workshop meeting (pp. 316-322).
[68]Kurz, A. (2008). Physiology of thermoregulation. Best Practice and and Research Clinical Anaesthesiology, 22(4), 627-644.
[69]Lasarov, W., Hoffmann, S., and and Orth, U. (2021). Vanishing Boycott Impetus: Why and How Consumer Participation in a Boycott Decreases Over Time. Journal of Business Ethics, 1-26.
[70]Lavorata, L. (2014). Influence of retailers’ commitment to sustainable development on store image, consumer loyalty and consumer boycotts: Proposal for a model using the theory of planned behavior. Journal of Retailing and Consumer Services, 21(6), 1021-1027.
[71]Lian, J., Zhang, F., Xie, X., and and Sun, G. (2017). Restaurant survival analysis with heterogeneous information. In Proceedings of the 26th International Conference on World Wide Web Companion (pp. 993-1002).
[72]Liang, L. S., Yi-Ren, L., and and Huang, A. H. M. (2017). OF THE TAIWENESE INTERNET. The Routledge Companion to Global Internet Histories, 182.
[73]Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of marketing, 70(3), 74-89.
[74]Loftus, G. R., and and Mackworth, N. H. (1978). Cognitive determinants of fixation location during picture viewing. Journal of Experimental Psychology: Human perception and performance, 4(4), 565.
[75]Luo, R., Xu, J., Zhang, Y., Ren, X., and and Sun, X. (2019). Pkuseg: A toolkit for multi-domain chinese word segmentation. arXiv preprint arXiv:1906.11455.
[76]Makarem, S. C., and and Jae, H. (2016). Consumer boycott behavior: An exploratory analysis of twitter feeds. Journal of consumer affairs, 50(1), 193-223.
[77]Mangold, W. G., and and Smith, K. T. (2012). Selling to Millennials with online reviews. Business Horizons, 55(2), 141-153.
[78]Miller, K. E., and and Sturdivant, F. D. (1977). Consumer responses to socially questionable corporate behavior: An empirical test. Journal of Consumer Research, 4(1), 1-7.
[79]Moghaddam, S., and and Ester, M. (2010, October). Opinion digger: an unsupervised opinion miner from unstructured product reviews. In Proceedings of the 19th ACM international conference on Information and knowledge management (pp. 1825-1828).
[80]Muliawan, A. D., Green, P. F., and and Robb, D. A. (2009). The turnover intentions of information systems auditors. International Journal of Accounting Information Systems, 10(3), 117-136.
[81]Mullen, T., and and Collier, N. (2004, July). Sentiment analysis using support vector machines with diverse information sources. In Proceedings of the 2004 conference on empirical methods in natural language processing (pp. 412-418).
[82]Myers, S. C. (1974). Interactions of corporate financing and investment decisions-implications for capital budgeting. The Journal of finance, 29(1), 1-25.
[83]Myllyneva, A., and and Hietanen, J. K. (2015). There is more to eye contact than meets the eye. Cognition, 134, 100-109.
[84]Nunnally, J. C. (1978). Psychometric Theory 2nd edition (New York: McGraw).
[85]Ohira, H., and and Hirao, N. (2015). Analysis of skin conductance response during evaluation of preferences for cosmetic products. Frontiers in psychology, 6, 103.
[86]O'Sullivan, D. (2001). The Interpretation of Qur'anic Text to Promote or Negate the Death Penalty for Apostates and Blasphemers. Journal of Qur'anic Studies, 3(2), 63-93.
[87]Ouyang, S., Li, C., and and Li, X. (2016). A peek into the future: Predicting the popularity of online videos. IEEE Access, 4, 3026-3033.
[88]Pang, B., Lee, L., and and Vaithyanathan, S. (2002). Thumbs up? Sentiment classification using machine learning techniques. arXiv preprint cs/0205070.
[89]Pang, B., Lee, L., and and Vaithyanathan, S. (2002). Thumbs up? Sentiment classification using machine learning techniques. arXiv preprint cs/0205070.
[90]Park, D. H., and and Kim, S. (2008). The effects of consumer knowledge on message processing of electronic word-of-mouth via online consumer reviews. Electronic commerce research and applications, 7(4), 399-410.
[91]Pieters, R., and and Warlop, L. (1999). Visual attention during brand choice: The impact of time pressure and task motivation. International Journal of research in Marketing, 16(1), 1-16.
[92]Post, J. E. (1985). Assessing the Nestlé boycott: Corporate accountability and human rights. California Management Review, 27(2), 113-131.
[93]Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological bulletin, 124(3), 372.
[94]Reinhardt, T., Schmahl, C., Wüst, S., and and Bohus, M. (2012). Salivary cortisol, heart rate, electrodermal activity and subjective stress responses to the Mannheim Multicomponent Stress Test (MMST). Psychiatry research, 198(1), 106-111.
[95]Risko, E. F., Richardson, D. C., and and Kingstone, A. (2016). Breaking the fourth wall of cognitive science: Real-world social attention and the dual function of gaze. Current Directions in Psychological Science, 25(1), 70-74.
[96]Rohrer, D., Pashler, H., and and Etchegaray, J. (1998). When two memories can and cannot be retrieved concurrently. Memory and and cognition, 26(4), 731-739.
[97]Salvucci, D. D., and and Goldberg, J. H. (2000, November). Identifying fixations and saccades in eye-tracking protocols. In Proceedings of the 2000 symposium on Eye tracking research and and applications (pp. 71-78).
[98]Shin, S., and and Yoon, S. W. (2018). Consumer motivation for the decision to boycott: The social dilemma. International Journal of Consumer Studies, 42(4), 439-447.
[99]Sirisuriya, D. S. (2015). A comparative study on web scraping.
[100]Solomon, J. (1998). Nike: Cool Goes Cold. NEWSWEEK-INTERNATIONAL EDITION-, 131, 38-39.
[101]Stauss, B. (2000). Using new media for customer interaction: a challenge for relationship marketing. In Relationship marketing (pp. 233-253). Springer, Berlin, Heidelberg.
[102]Steinfeld, N., Samuel-Azran, T., and and Lev-On, A. (2016). User comments and public opinion: Findings from an eye-tracking experiment. Computers in human behavior, 61, 63-72.
[103]Suhud, U. (2018). The impact of consumer animosity on purchase unwillingness in a boycott of Sari Roti. Binus Business Review, 9(2), 87-94.
[104]Tan, A. H. (1999, April). Text mining: The state of the art and the challenges. In Proceedings of the pakdd 1999 workshop on knowledge disocovery from advanced databases (Vol. 8, pp. 65-70).
[105]Tankard, J. W. (2001). The empirical approach to the study of media framing. Framing public life: Perspectives on media and our understanding of the social world, 95-106.
[106]Taranovich, S. (2016). Data center next generation power supply solutions for improved efficiency. EDN network, April.
[107]Underwood, B. J., and and Shaughnessy, J. J. (1975). Experimentation in psychology.
[108]Vahey, R., and and Becerra, R. (2015). Galvanic skin response in mood disorders: a critical review.
[109]Van der Stigchel, S., Hessels, R. S., van Elst, J. C., and and Kemner, C. (2017). The disengagement of visual attention in the gap paradigm across adolescence. Experimental Brain Research, 235(12), 3585-3592.
[110]Vila, J., and and Gomez, Y. (2016). Extracting business information from graphs: An eye tracking experiment. Journal of Business Research, 69(5), 1741-1746.
[111]Villarejo, M. V., Zapirain, B. G., and and Zorrilla, A. M. (2012). A stress sensor based on Galvanic Skin Response (GSR) controlled by ZigBee. Sensors, 12(5), 6075-6101.
[112]Viviani, P. (1990). Eye movements in visual search: Cognitive, perceptual, and motor control aspects. Eye movements and their role in visual and cognitive processes, 353-383.
[113]Williams, L. M., Loughland, C. M., Green, M. J., Harris, A. W., and and Gordon, E. (2003). Emotion perception in schizophrenia: an eye movement study comparing the effectiveness of risperidone vs. haloperidol. Psychiatry research, 120(1), 13-27.
[114]Yang, T. (2012). The decision behavior of Facebook users. Journal of Computer Information Systems, 52(3), 50-59.
[115]Yarbus, A. L. (1967). Eye movements during perception of complex objects. In Eye movements and vision (pp. 171-211). Springer, Boston, MA.
[116]Yu, H., and and Hatzivassiloglou, V. (2003). Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences. In Proceedings of the 2003 conference on Empirical methods in natural language processing (pp. 129-136).
[117]Zhan, J., Loh, H. T., and and Liu, Y. (2009). Gather customer concerns from online product reviews–A text summarization approach. Expert Systems with Applications, 36(2), 2107-2115.
[118]Zhang, L., Li, X. P., Zhang, F. B., and and Hu, B. (2017). research on keyword extraction and sentiment orientation analysis of educational texts. Journal of Computers, 28(6), 301-313.
[119]Zhang, M. J., and and Lee, S. S. (2018). Influences of boycott-related characteristics and consumer citizenship on online boycott attitude and intention: Focusing on moderating effects of self-monitoring. Consumer Policy and Education Review, 14 (1), 1-26.
[120]Zhang, W., Yoshida, T., and and Tang, X. (2011). A comparative study of TF* IDF, LSI and multi-words for text classification. Expert Systems with Applications, 38(3), 2758-2765.