Content analysis and message characteristics of Twitter: a case study of high-end makeup
Contenido principal del artículo
Resumen
Descargas
Detalles del artículo
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.
Esta revista proporciona un acceso abierto a su contenido, basado en el principio de ofrecer al público un acceso libre a las investigaciones ayuda a un mayor intercambio global del conocimiento. De igual forma su versión impresa es de libre acceso y no tiene costos asociados por publicación.
Citas
Amatulli, C., Guido, G. & Nataraajan, R. (2015). Luxury purchasing among older consumers: exploring inferences about cognitive age, status, and style motivations. Journal of Business Research, 68(9), 1945-1952. https://www.sciencedirect.com/science/article/pii/S01482963150 00053?casa_token=xVrpaL7cGAkAAAAA:cOerwIZw19SYmBJp0kbRqc30udpH9cad30hzZscCcNUW09YUBQvUVF1e-2-f657gJb7ezHbe9w
Annie, S. (2012). The potential of social media for luxury brand management. Marketing Intelligence & Planning, 30(7), 687-699. https://www.emerald.com/insight/content/doi/10.1108/0263 4501211273805/full/html?casa_token=avH6_gkNtJYAAAAA:Yoahzh_n6CONaFNKWONqGPfGiRvkL9kQ0OFHLtq2_xwjWYSSlmmm0-YjUWFkgOIFQx6ROwczIMl3xWuWIcojWV17 zvsQzJFXSSn8YvkdemGvGKWlMmk
Balazs, J. A. & Velásquez, J. D. (2016). Opinion mining and information fusion: a survey. Information Fusion, 27, 95-110. https://www.sciencedirect.com/science/article/pii/S15662535150005 36?casa_token=u5X28txOn1cAAAAA:7eEeoOqnTLFTpJIlWFu9FhABEXvodnu6-tO3ojHaNTAnE0tWuTxvOfZTRGv6NSQc04_M0RqSHA
Bello, G., Hernandez, J. & Camacho, D. (2017). Detecting discussion communities on vaccination in Twitter. Future Generation Computer Systems, 66, 125-136. https://www.sciencedirect.com/science/article/pii/S0167739X16302175?casa_token=wyUyhWBMREAAAAAA:n2nibQ1mGzl3Yjg1j305aEzSLmEOLSLAc7friUxdmW2S2TLlAXan-p8SFYIZMV7178umHkjRjw
Bello, G., Jung, J. & Camacho, D. (2016). Social big data: Recent achievements and new challenges. Information Fusion, 28, 45-59. https://www.sciencedirect.com/science/article/pii/S 1566253515000780?casa_token=emJ3kf4ZtfYAAAAA:QpNKs3J-R9PN94JFoTdy0hZ3ffxywr2-DqIjy2OjRPV6D1aB_9CWWF5h1Fv5t9ks8bNJzq-T9A
Bennett, W. & Segerberg, A. (2012). The logic of connective action: Digital media and the personalization of contentious politics. Information, Communication & Society, 15(5), 739-768. https://doi.org/10.1080/1369118X.2012.670661
Boero, M. (2015). The language of fashion in postmodern society: A social semiotic perspective. Semiotica, 2015(207), 303-325. https://doi.org/10.1515/sem-2015-0037
Brant, A. (2016). Using an Algorithm to Figure Out What Luxury Customers Really Want. Harvard Business Review.. https://hbr.org/2016/07/using-an-algorithm-to-figure-out-what-luxury-customers-really-want
Cha, M., Haddadi, H., Benevenuto, F. & Gummadi, P. K. (2010). Measuring user influence in Twitter: The million follower fallacy. Icwsm, 10(10-17), 30. https://ojs.aaai.org/index.p hp/ICWSM/article/view/14033
Christakis, N. & Fowler, J (2013). Social contagion theory: examining dynamic social networks and human behavior. Statistics in medicine, 32(4), 556-577. https://www.ncbi.nlm.nih.gov /pmc/articles/PMC3830455/
Deloitte. (2014). Global Power of Luxury Goods: in the hands of the consumer. https://www2.deloitte.com/tr/en/pages/consumer-business/articles/global-powers-of-luxury-goods-2014.html
Demattè, M., Sanabria, D. & Spence, C. (2007). Olfactory–tactile compatibility effects demonstrated using a variation of the Implicit Association Test. Acta psychologica, 124(3), 332-343. https://www.sciencedirect.com/science/article/pii/S0001691806000527?casa_token=3vDxnLV92U8AAAAA:c46jSRY6cRYOlOKWLHQBhnSUdst8dLDX0LeELxfKB7G7N2kaLZE-E7Ne_Nc7btY5ReD-dsGMRg
Feng, D. & O’Halloran, K. (2012). Representing emotive meaning in visual images: A social semiotic approach. Journal of Pragmatics, 44(14), 2067-2084. https://www.sciencedirect.com/science /article/pii/S0378216612002603?casa_token=z_0slUTzduEAAAAA:E8JnPMA64QcoLEgVDWXbQU2XkQzQ-CARs0eDOn5aUvz8lmt-wKpUTyhQEAjt26ztVEITU97gDQ
Freberg, K., Graham, K., McGaughey, K. & Freberg, L. (2011). Who are the social media influencers? A study of public perceptions of personality. Public Relations Review, 37(1), 90-92. https://www.sciencedirect.com/science/article/pii/S0363811110001207?casa_token=wwaMvBq2GvUAAAAA:ZWwjz00gDBNdrV04v9TMGnCJ5yAdzSQjeMRleVlI57YWzWtRC3tcakWyRoLLoQ8QC2ZhqzquOQ
Gandomi, A. & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144. https://www.sciencedirect.com/science/article/pii/S0268401214001066
Gul, S., Mahajan, I., Nisa, N., Tariq, S., Jan, A. & Ahmad, S. (2016). Tweets speak louder than leaders and masses: An analysis of tweets about the Jammu and Kashmir elections 2014. Online Information Review, 40(7), 900-912. https://doi.org/10.1108/OIR-10-2015-0330
Hachaj, T. & Ogiela, M. (2017). Clustering of trending topics in microblogging posts: A graph-based approach. Future Generation Computer Systems, 67, 297-304. https://doi.org/10.1016 /j.future.2016.04.009
Hoe, D. & Lee, C. (2011). An analysis of tweets in response to the death of Michael Jackson. Aslib Proceedings. 63(5), 432-444. https://doi.org/10.1108/00012531111164941
Hosch, B., Amrit, C., Aarts, K. & Dassen, A. (2016). How do online citizens persuade fellow voters? Using Twitter during the 2012 Dutch parliamentary election campaign. Social science computer review, 34(2), 135-152. https://doi.org/10.1177/0894439314558200
Houghton, D., Joinson, A., Caldwell, N. & Marder, B. (2013). Tagger’s delight? Disclosure and liking in Facebook: the effects of sharing photographs amongst multiple known social circles. Birmingham Business School: Discussion Paper Series. https://www.econstor.eu/handle/10419/202647
Hutter, K., Hautz, J., Dennhardt, S. & Füller, J. (2013). The impact of user interactions in social media on brand awareness and purchase intention: the case of MINI on Facebook. Journal of Product & Brand Management, 22(5/6), 342-351. https://doi.org/10.1108/JPBM-05-2013-0299
Hsieh, H. F. & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative health research, 15(9), 1277-1288. https://doi.org/10.1177/1049732305276687
Jansen, B., Zhang, M., Sobel, K. & Chowdury, A. (2009). Twitter power: Tweets as electronic word of mouth. Journal of the American society for information science and technology, 60(11), 2169-2188. https://doi.org/10.1002/asi.21149
Khan, F., Bashir, S. & Qamar, U. (2014). TOM: Twitter opinion mining framework using hybrid classification scheme. Decision Support Systems, 57, 245-257. https://doi.org/10.1016/j.dss.2013.09.004
Kosinski, M., Stillwell, D. & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15), 5802-5805. https://doi.org/10.1073/pnas.1218772110
Krippendorff, K. (2012). Content analysis: An introduction to its methodology. Sage Publications. https://books.google.com.co/books?hl=es&lr=&id=s_yqFXnGgjQC&oi=fnd&pg=PP1&ots=b3ZS-UolyV&sig=hCMQSPTxzl-dUxoH5AxMfwPeHgs&redir_esc=y#v=onepage&q&f=false
Kulsiri, P. (2012). Self-Concept, Locus of Control, Media Exposure, And Behavior of Youth Toward Luxury Products Purchase. Journal of Business & Economics Research
[Online], 10(1), 11. https://www.clutejournals.com/index.php/JBER/article/view/6729
Lambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1-14. https://www.tandfonline.com/doi/abs /10.1080/00401706.1992.10485228
Lemon, K. & Verhoef, P. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96. https://doi.org/10.1509/jm.15.0420
Li, J., Peng, W., Li, T. & Sun, T. (2013, April). Social network user influence dynamics prediction. Asia-Pacific Web Conference. 2013. Springer, Berlin, Heidelberg. https://link.springer.com/chapter/10.1007/978-3-642-37401-2_32
McCormick, H. & Livett, C. (2012). Analysing the influence of the presentation of fashion garments on young consumers’ online behaviour. Journal of Fashion Marketing and Management: An International Journal, 16(1), 21-41. https://doi.org/10.1108/13612021211203014
Mullahy, J. (1986). Specification and testing of some modified count data models. Journal of econometrics, 33(3), 341-365. https://doi.org/10.1016/0304-4076(86)90002-3
Neves, A., Vieira, R., Mourão, F. & Rocha, L. (2015). Quantifying Complementarity among Strategies for Influencers’ Detection on Twitter. Procedia Computer Science, 51, 2435-2444. https://doi.org/10.1016/j.procs.2015.05.428
Osuna, I. & Pinzón, C. (2017). Comportamiento y experiencia de consumo desde la interconexión e interactividad de la World Wide Web: un recorrido teórico. I+D REVISTA DE INVESTIGACIONES, 8(2) 35-45. https://doi.org/10.33304/revinv.v08n2-2016004.
Oswald, L. & Oswald, L. (2012). Marketing semiotics: Signs, strategies, and brand value. Oxford University Press. https://books.google.com.co/books?hl=es&lr=&id=42IQnidxP8IC&oi= fnd&pg=PP1&dq=Marketing+semiotics:+Signs,+strategies,+and+brand+value&ots=N88xPpCCpD&sig=aBmkv0KjE0c78DY8m5kWSyT2ENY&redir_esc=y#v=onepage&q=Marketing%20semiotics%3A%20Signs%2C%20strategies%2C%20and%20brand%20value&f=false
Parguel, B., Delécolle, T. & Valette-Florence, P. (2016). How price display influences consumer luxury perceptions. Journal of Business Research, 69(1), 341-348. https://doi.org/10.1016/j.jbusres.2015.08.006
Pinzón, C., Osuna, I. & Jaramillo, L. (2018). Digital Marketing Strategies for Luxury Cosmetics Brands: Latin America’s Case–Colombia. In Ozuem, W. & Azemi, Y. Digital Marketing Strategies for Fashion and Luxury Brands. (1st ed., pp. 126-144). IGI Global. https://books.google.com.co/books?hl=es&lr=&id=z-Y7DwAAQBAJ&oi=fnd&pg=PR1&dq= Digital+Marketing+Strategies+for+Fashion+and+Luxury+Brands&ots=gDKmBD5L5E&sig=TqTDBqac2ebNkDbDlQA2_OYGqzQ&redir_esc=y#v=onepage&q=Digital%20Marketing%20Strategies%20for%20Fashion%20and%20Luxury%20Brands&f=false
Powers, T., Advincula, D., Austin, M., Graiko, S. & Snyder, J. (2012). Digital and social media in the purchase decision process. Journal of advertising research, 52(4), 479-489. 10.2501/JAR-52-4-479-489
Reilly, C., Salinas, D. & De Leon, D. (2014, March 10-13). Ranking users based on influence in a directional social network. Computational Science and Computational Intelligence (CSCI), 2014 International Conference. Las Vegas, USA. 10.1109/CSCI.2014.127
Richardson, A. (2010). Using customer journey maps to improve customer experience. Harvard Business Review, 15(1). http://www.iimagineservicedesign.com/wp-content/uploads/2015/09/Using-Customer-Journey-Maps-to-Improve-Customer-Experience.pdf
Riff, D., Lacy, S. & Fico, F. (2014). Analyzing media messages: Using quantitative content analysis in research. Routledge. https://doi.org/10.4324/9780429464287
Rokka, J. (2015). Self-Transformation and Performativity of Social Media Images. NA-Advances in Consumer Research, 43. https://www.acrwebsite.org/volumes/1019697/volumes/v43/NA-43
Smith, A., Fischer, E. & Yongjian, C. (2011). Differences in brand-related user-generated content across three social media sites: An inductive content analysis. NA-Advances in Consumer Research, 39, 766. https://www.acrwebsite.org/volumes/1009529/volumes/v39/NA-39
Smith, A., Fischer, E. & Yongjian, C. (2012). How does brand-related user-generated content differ across YouTube, Facebook, and Twitter? Journal of Interactive Marketing, 26(2), 102-113. https://doi.org/10.1016/j.intmar.2012.01.002
Steinmann, S., Mau, G. & Schramm‐Klein, H. (2015). Brand communication success in online consumption communities: An experimental analysis of the effects of communication style and brand pictorial representation. Psychology & Marketing, 32(3), 356-371. https://doi.org/10.1002/mar.20784
Stieglitz, S. & Dang-Xuan, L. (2013). Emotions and information diffusion in social media—sentiment of microblogs and sharing behavior. Journal of Management Information Systems, 29(4), 217-248. https://doi.org/10.2753/MIS0742-1222290408
Think With Google. (2013). Introducing Gen C: The YouTube Generation. https://ssl.gstatic.com/think/docs/introducing-gen-c-the-youtube-generation_research-studies.pdf
Twitter. (2016) Privacy policy. https://twitter.com/privacy?lang=es
Vidal, L., Ares, G. & Jaeger, S. (2016). Use of emoticon and emoji in tweets for food-related emotional expression. Food Quality and Preference, 49, 119-128. https://doi.org/10.1016/j.foodqual.2015.12.002
Vidal, L., Ares, G., Machín, L. & Jaeger, S. (2015). Using Twitter data for food-related consumer research: A case study on “what people say when tweeting about different eating situations.” Food Quality and Preference, 45, 58-69. https://doi.org/10.1016/j.foodqual.2015.05.006
Wang, R., Liu, W. & Gao, S. (2016). Hashtags and information virality in networked social movement: Examining hashtag co-occurrence patterns. Online Information Review, 40(7), 850-866.
Wiedmann, K., Hennigs, N. & Siebels, A. (2009). Value‐based segmentation of luxury consumption behavior. Psychology & Marketing, 26(7), 625-651. https://doi.org/10.1002/mar.20292
Zhang, J. & Mao, E. (2016). From online motivations to ad clicks and to behavioral intentions: An empirical study of consumer response to social media advertising. Psychology & Marketing, 33(3), 155-164. https://doi.org/10.1002/mar.20862