參考文獻 |
Data Reportal. (Jan, 2021). DIGITAL 2021: GLOBAL OVERVIEW REPORT., Retrieved from: https://datareportal.com/reports/digital-2021-global-overview-report
Data Reportal. (Jan, 2021). DIGITAL 2021: TAIWAN., Retrieved from: https://datareportal.com/reports/digital-2021-global-overview-report
Google Cloud Vision API, Retrieved from: https://cloud.google.com/vision?hl=zh_tw
Ahtola, Olli T. (1985). “Hedonic and utilitarian aspects of consumer behavior: An attitudinal perspective”, ACR North American Advances , Vol. 21, pp.7-10.
Alowibdi, J. S, Buy, B. A and Yu, P. (2013). “Empirical evaluation of profile characteristics for gender classification on twitter.” 2013 12th International Conference on Machine Learning and Applications, IEEE.
Alowibdi, J. S, Buy, B. A and Yu, P. (2013). “Language independent gender classification on Twitter.”Proceedings of the 2013 IEEE/ACM international conference on advances in social networks analysis and mining.
Applebaum, W. (1951). “Studying customer behavior in retail stores”, Journal of marketing, Vol. 16, No. 2, pp.172-178.
Babin, B. J, Darden, W. R, and Griffin, M. (1994). “Work and/or fun: measuring hedonic and utilitarian shopping value”, Journal of consumer research, Vol. 20, No. 4, pp.644-656.
Barnes, S. J and Pressey, A. D. (2012). “In search of the “Meta‐Maven”: An examination of market maven behavior across real‐life, web, and virtual world marketing channels.” Psychology & Marketing, Vol. 29, No. 3, pp. 167-185.
Belk, R. W. (1984). “Three scales to measure constructs related to materialism: Reliability, validity, and relationships to measures of happiness”, Advances in Consumer Research, Vol. 11, Issue 1, pp. 291-297.
Bellenger, D. N, Robertson, D. H and Greenberg, B. A. (1977). “Shopping center patronage motives.” Journal of retailing, Vol. 53, No. 2, pp. 29-38.
Brancaleone, V. and Gountas, J. (2007). “Personality characteristics of market mavens”, North American - Advances in Consumer Research, Vol. 34.
Bussière, D. (2015). “Understanding the Market Maven: Personal and Social Characteristics.” In Proceedings International Marketing Trends Conference, pp. 1-18.
Chandon, P., Wansink, B. and Laurent, G. (2000). “A benefit congruency framework of sales promotion effectiveness”, Journal of marketing, Vol. 64, Issue 4, pp. 65-81.
Clover, V. T. (1950). “Relative importance of impulse-buying in retail stores”, Journal of marketing, Vol. 15, No. 1, pp. 66-70.
Darden, W. R, and Perreault Jr, W. D. (1976). “Identifying interurban shoppers: Multiproduct purchase patterns and segmentation profiles”, Journal of marketing research, Vol. 13, No. 1, pp. 51-60.
Darden, W. R and Reynolds, F. D. (1971). “Shopping orientations and product usage rates”, Journal of Marketing Research, Vol. 8, No. 4, pp. 505-508.
Darley, W. and Lim, J. S. (2018). “Mavenism and e-maven propensity: antecedents, mediators and transferability.” Journal of Research in Interactive Marketing, Vol. 12, No. 3, pp. 293-308.
Daun, Ake. (1983). “The materialistic life-style: Some socio-psychological aspects”, Consumer behavior and environmental quality, pp. 1-6.
Dodds, W. B, Monroe, K.B and Grewal, D. (1991). “Effects of price, brand, and store information on buyers product evaluations”, Journal of marketing research, Vol. 28, No. 3, pp. 307-319.
Duan, J. and Dholakia, R. R. (2018). “How purchase type influences consumption-related posting behavior on social media: The moderating role of materialism”, Journal of Internet Commerce, Vol. 17, Issue 1, pp. 64-80.
Feick, L. F, and Price, L. L. (1987). “The market maven: A diffuser of marketplace information”, Journal of marketing, Vol. 51, pp. 83-97.
Fernández, D., Moctezuma D. and Siordia, O. S. (2016). “Features combination for gender recognition on Twitter users.” 2016 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), pp. 1-6. IEEE.
Ferwerda, B., Schedl M. and Tkalcic, M. (2016). “Using instagram picture features to predict users’ personality.” International Conference on Multimedia Modeling, pp. 850-861. Springer.
Gao, R., Hao B., Bai S., Li L., Li A. and Zhu, T. (2013). “Improving user profile with personality traits predicted from social media content.” Proceedings of the 7th ACM conference on recommender systems, pp. 355-358.
Golbeck, J., Robles C., Edmondson M. and Turner, K. (2011). “Predicting personality from twitter.” In 2011 IEEE Third International Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third International Conference on Social Computing, pp. 149-156. IEEE.
Golbeck, J., Robles C. and Turner, K. 2011. “Predicting personality with social media.” CHI”11 extended abstracts on human factors in computing systems.
Guido, Gianluigi. (2006). “Shopping motives, big five factors, and the hedonic/utilitarian shopping value: An integration and factorial study”, Innovative Marketing, Vol. 2, pp. 57-67.
Han, K., Jo, Y., Jeon, Y., Kim, B., Song, J. and Kim, S. W. (2018). “Photos don’t have me, but how do you know me? Analyzing and predicting users on Instagram.” Adjunct publication of the 26th conference on user modeling, adaptation and personalization, pp. 251-256.
Han, K., Lee, S., Jang J. Y., Jung, Y. and Lee, D. (2016). “Teens are from mars, adults are from venus: analyzing and predicting age groups with behavioral characteristics in instagram.” Proceedings of the 8th ACM Conference on Web Science, pp. 35-44.
Harrigan, P., Daly, T.M, Coussement, K., Lee, J.A, Soutar, G.N and Evers, U. (2021). “Identifying influencers on social media”, International Journal of Information Management, Vol. 56, 102246.
Iyer, G. R, Blut, M., Xiao, S. H. and Grewal, D. (2020). “Impulse buying: a meta-analytic review”, Journal of the Academy of Marketing Science, Vol. 48, pp. 384-404.
Jeon, Y., Jeon, S. G. and Han, K. (2020). “Better targeting of consumers: Modeling multifactorial gender and biological sex from Instagram posts”, User Modeling and User-Adapted Interaction, Vol. 30, pp. 833-866.
Kesari, B. and Atulkar, S. (2016). “Satisfaction of mall shoppers: A study on perceived utilitarian and hedonic shopping values”, Journal of Retailing and Consumer services, Vol. 31, pp. 22-31.
Kubany, A., Ishay, S. B., Ohayon, R. S., Shmilovici, A., Rokach, L. and Doitshman, T. (2020). “Comparison of state-of-the-art deep learning APIs for image multi-label classification using semantic metrics”, Expert Systems with Applications, Vol. 161, Article 113656.
Lee, M. SW and Ahn, C. S. Y. (2016). “Anti‐consumption, materialism, and consumer well‐being”, Journal of Consumer Affairs, Vol. 50, Issue 1, pp. 18-47.
Li, H., Kuo, C. and Rusell, M. G. (1999). “The impact of perceived channel utilities, shopping orientations, and demographics on the consumer”s online buying behavior”, Journal of computer-mediated communication, Vol. 5, Issue 2, JCMC521.
Marquardt, J., Farnadi, G., Vasudevan, G., Moens, M.F., Davalos, S., Teredesai, A. and Martine D. C. (2014). “Age and gender identification in social media”, Proceedings of CLEF 2014 Evaluation Labs, 1180, pp. 1129-1136.
Ohanian, R., and Tashchian A. (1992). “Consumers shopping effort and evaluation of store image attributes: the roles of purchasing involvement and recreational shopping interest”, Journal of Applied Business Research (JABR), Vol. 8, pp. 40-49.
Olsen, S. O., Tudoran, A. A., Honkanen, P. and Verplanken, B. (2016). “Differences and similarities between impulse buying and variety seeking: A personality‐based perspective”, Psychology & Marketing, Vol. 33, Issue 1, pp. 36-47.
Peersman, C., Daelemans, W. and Van Vaerenbergh, L. (2011). “Predicting age and gender in online social networks.” Proceedings of the 3rd international workshop on Search and mining user-generated contents, pp. 37-44.
Pennacchiotti, M. and Popescu, A. M. (2011). “A machine learning approach to twitter user classification.” International Conference on Weblogs and Social Media.
Rao, D., Yarowsky, D., Shreevats, A. and Gupta, M. (2010). “Classifying latent user attributes in twitter.” Proceedings of the 2nd international workshop on Search and mining user-generated contents, pp. 37-44.
Rassuli, K. M, and Hollander, S. C. (1986). “Desire-induced, innate, insatiable?”, Journal of Macromarketing, Vol. 6, pp. 4-24.
Reynaldo, N, Chanrico, W., Suhartono, D. and Purnomo, F. (2019). “Gender Demography Classification on Instagram based on User”s Comments Section”, Procedia Computer Science, Vol. 157, pp. 64-71.
Reynolds, K. E and Beatty, S. E. (1999). “Customer benefits and company consequences of customer-salesperson relationships in retailing”, Journal of retailing, Vol. 75, Issue 1, pp. 11-32.
Richins, M. L and Dawson, S. (1992). “A consumer values orientation for materialism and its measurement: Scale development and validation”, Journal of consumer research, Vol. 19, pp. 303-316.
Rook, Dennis W. (1987). “The buying impulse”, Journal of consumer research, Vol. 14, Issue 1, pp. 189-199.
Schultz, L. and Adams, M. (2018). “Evaluation of Google Vision API for Object Detection in General Subject Images.” Proceedings of the Conference on Information Systems Applied Research.
Schwartz, H A., Eichstaedt, J. C , Kern, M. L, Dziurzynski, L., Ramones, S. M, Agrawal, M., Shah, A., Kosinski, M., Stillwell, D. and Seligman, M. EP. (2013). “Personality, gender, and age in the language of social media: The open-vocabulary approach”, PloS one, Vol. 8.
Singh, J., Wheeler, J., Fong, N. and Chaudhary, S. “A Comparison of Public Cloud Computer Vision Services”.
Stern, Hawkins. (1962). “The significance of impulse buying today”, Journal of marketing, Vol. 26, No. 2, pp. 59-62.
Stone, Gregory P. (1954). “City shoppers and urban identification: observations on the social psychology of city life”, American Journal of Sociology, Vol. 60, No. 1, pp. 36-45.
Verplanken, B. and Herabadi, A. (2001). “Individual differences in impulse buying tendency: Feeling and no thinking”, European Journal of personality, Vol. 15, S71-S83.
Vicente, M., Batista, F. and Carvalho, J. P. (2019). “Gender detection of Twitter users based on multiple information sources.” Interactions Between Computational Intelligence and Mathematics Part 2 (Springer), pp. 39-54.
Vicente, M., Batista, F. and Carvalho, J. P. (2015). “Twitter gender classification using user unstructured information.” In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1-7. IEEE.
Wang, L., Li, Q., Chen, X. and Li, S. (2016). “Multi-task learning for gender and age prediction on chinese microblog.” Natural Language Understanding and Intelligent Applications (Springer).
Workman, J. E, Lee, S. H. and Liang, Y. (2020). “Social Media Engagement, Gender, Materialism, and Money Attitudes.” In International Textile and Apparel Association Annual Conference Proceedings, Vol. 77, No. 1, Iowa State University Digital Press.
Yang, Hongwei. (2013). “Market mavens in social media: Examining young Chinese consumers’ viral marketing attitude, eWOM motive, and behavior”, Journal of Asia-Pacific Business, Vol. 14, Issue 2, pp. 154-178.
You, Q., Bhatia, S., Sun, T. and Luo, J. (2014). “The eyes of the beholder: Gender prediction using images posted in online social networks.” 2014 IEEE International Conference on Data Mining Workshop, pp. 1026-1030. IEEE.
Yu, C. and Bastin, M. (2017). “Hedonic shopping value and impulse buying behavior in transitional economies: A symbiosis in the Mainland China marketplace.” Advances in Chinese Brand Management (Springer), pp. 316-330.
王培倫,「星座對於消費者在購物傾向上之影響-以大台北地區大學生為例」,國立政治大學,碩士論文,民國92年。 |