Jaehyuk Park
Giovanni Luca Ciampaglia
Emilio Ferrara
ABSTRACT
Fashion is a multi-billion dollar industry with social and economic implications worldwide. To gain popularity, brands want to be represented by the top popular models. As new faces are selected using stringent (and often criticized) aesthetic criteria, a priori predictions are made difficult by information cascades and other fundamental trend-setting mechanisms. However, the increasing usage of social media within and without the industry may be affecting this traditional system. We therefore seek to understand the ingredients of success of fashion models in the age of Instagram. Combining data from a comprehensive online fashion database and the popular mobile image-sharing platform, we apply a ma- chine learning framework to predict the tenure of a cohort of new faces for the 2015 Spring/Summer season throughout the subsequent 2015-16 Fall / Winter season. Our framework successfully predicts most of the new popular models who appeared in 2015. In particular, we find that a strong social media presence may be more important than being under contract with a top agency, or than the aesthetic standards sought after by the industry.
- Nazanin Andalibi, Pinar Ozturk, and Andrea Forte. 2015. Depression-related Imagery on Instagram. In Proceedings of the 18th ACM Conference Companion on Computer Supported Cooperative Work & Social Computing. ACM, 231–234. Google Scholar
Digital Library
- Patrik Aspers and Frédéric Godart. 2013. Sociology of Fashion: Order and Change. Annual Review of Sociology 39, 1 (2013), 171–192.Google ScholarCross Ref
- Sitaram Asur, Bernardo A Huberman, Gabor Szabo, and Chunyan Wang. 2011. Trends in Social Media: Persistence and Decay. In Fifth International AAAI Conference on Weblogs and Social Media.Google Scholar
- Sitaram Asur and Bernardo A Huberman. 2010. Predicting the future with social media. In Web Intelligence and Intelligent Agent Technology (WI-IAT), 2010 IEEE/WIC/ACM International Conference on, Vol. 1. IEEE, 492–499. Google ScholarDigital Library
- Sushil Bikhchandani, David Hirshleifer, and Ivo Welch. 1992. A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of political Economy (1992), 992–1026.Google Scholar
- Leo Breiman. 2001. Random forests. Machine learning 45, 1 (2001), 5–32. Google ScholarDigital Library
- Leah Cassidy and Kate Fitch. 2013. Beyond the catwalk: Fashion public relations and social media in Australia. Asia Pacfic Public Relations Journal 15, 1 (2013).Google Scholar
- Giovanni Luca Ciampaglia, Alessandro Flammini, and Filippo Menczer. 2015. The production of information in the attention economy. Scientfic Reports 5 (2015), 9452.Google ScholarCross Ref
- Pasquale De Meo, Emilio Ferrara, Giacomo Fiumara, and Alessandro Provetti. 2014. On Facebook, most ties are weak. Commun. ACM 57, 11 (2014), 78–84. Google ScholarDigital Library
- Marie-Laure Djelic and Antti Ainamo. 1999. The coevolution of new organizational forms in the fashion industry: a historical and comparative study of France, Italy, and the United States. Organization Science 10, 5 (1999), 622–637. Google ScholarDigital Library
- Emilio Ferrara, Roberto Interdonato, and Andrea Tagarelli. 2014. Online popularity and topical interests through the lens of instagram. In Proceedings of the 25th ACM conference on Hypertext and social media. ACM, 24–34. Google ScholarDigital Library
- Emilio Ferrara, Mohsen JafariAsbagh, Onur Varol, Vahed Qazvinian, Filippo Menczer, and Alessandro Flammini. 2013a. Clustering memes in social media. In 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. IEEE, 548–555. Google ScholarDigital Library
- Emilio Ferrara, Onur Varol, Filippo Menczer, and Alessandro Flammini. 2013b. Traveling trends: social butterflies or frequent fliers?. In Proceedings of the first ACM conference on Online social networks. ACM, 213–222. Google ScholarDigital Library
- T. S. Fox. 2014. How Instagram is Changing Fashion Week. (February 2014). http://hypebeast.com/2014/ 2/how-instagram-is-changing-fashion-week {Online; posted 14-February-2014}.Google Scholar
- Georg Franck. 1999. Scientfic Communication–A Vanity Fair? Science 286, 5437 (1999), 53–55.Google Scholar
- Yoav Freund and Robert E Schapire. 1995. A desicion-theoretic generalization of on-line learning and an application to boosting. In Computational learning theory. Springer, 23–37. Google ScholarDigital Library
- Cheryl D Fryar, Qiuping Gu, and Cynthia L Ogden. 2012. Anthropometric reference data for children and adults: United States, 2007-2010. Vital and health statistics. Series 11, Data from the national health survey 252 (2012), 1–48.Google Scholar
- Eric Gilbert, Saeideh Bakhshi, Shuo Chang, and Loren Terveen. 2013. 'I Need to Try This'?: A Statistical Overview of Pinterest. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '13). ACM, New York, NY, USA, 2427–2436. Google ScholarDigital Library
- Frédéric C Godart and Ashley Mears. 2009. How do cultural producers make creative decisions? Lessons from the catwalk. Social Forces 88, 2 (2009), 671–692.Google ScholarCross Ref
- Lisa Green, Olivier Zimmer, and Yarden Horwitz. 2015. Google Fashion Trends Report (U.S.). (2015). https://www.thinkwithgoogle.com/features/ spring-2015-fashion-trends-google-data.html Accessed 2015-05-18.Google Scholar
- Thomas Hillman and Alexandra Weilenmann. 2015. Situated Social Media Use: A Methodological Approach to Locating Social Media Practices and Trajectories. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). ACM, New York, NY, USA, 4057–4060. Google ScholarDigital Library
- CJ Hutto and Eric Gilbert. 2014. Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Eighth International AAAI Conference on Weblogs and Social Media.Google ScholarCross Ref
- Mohsen JafariAsbagh, Emilio Ferrara, Onur Varol, Filippo Menczer, and Alessandro Flammini. 2014. Clustering memes in social media streams. Social Network Analysis and Mining 4, 1 (2014), 1–13.Google ScholarCross Ref
- Yuniya Kawamura. 2004. Fashion-ology: an introduction to fashion studies. Berg.Google Scholar
- Jan H. Kietzmann, Kristopher Hermkens, Ian P. McCarthy, and Bruno S. Silvestre. 2011. Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons 54, 3 (2011), 241–251.Google ScholarCross Ref
- Angella J Kim and Eunju Ko. 2012. Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research 65, 10 (2012), 1480–1486.Google ScholarCross Ref
- Peter Klemperer, Yuan Liang, Michelle Mazurek, Manya Sleeper, Blase Ur, Lujo Bauer, Lorrie Faith Cranor, Nitin Gupta, and Michael Reiter. 2012. Tag, you can see it!: using tags for access control in photo sharing. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 377–386. Google ScholarDigital Library
- Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon. 2010. What is Twitter, a social network or a news media?. In Proceedings of the 19th international conference on World wide web. ACM, 591–600. Google ScholarDigital Library
- Yusan Lin, Heng Xu, Yilu Zhou, and Wang-Chien Lee. 2015. Styles in the Fashion Social Network: An Analysis on Lookbook.nu. In Social Computing, Behavioral-Cultural Modeling, and Prediction. Springer, 356–361.Google Scholar
- Yusan Lin, Yilu Zhou, and Heng Xu. 2014. The Hidden Influence Network in the Fashion Industry. In The 24th Annual Workshop on Information Technologies and Systems (WITS).Google Scholar
- Yusan Lin, Yilu Zhou, and Heng Xu. 2015. Text-Generated Fashion Influence Model: An Empirical Study on Style.com. In 48th Hawaii International Conference on System Sciences, HICSS 2015, Kauai, Hawaii, USA, January 5-8, 2015. 3642–3650. Google ScholarDigital Library
- Ashley Mears. 2011. Pricing beauty: The making of a fashion model. Univ of California Press.Google Scholar
- Ashley Mears and William Finlay. 2005. Not Just a Paper Doll How Models Manage Bodily Capital and Why They Perform Emotional Labor. Journal of Contemporary Ethnography 34, 3 (2005), 317–343.Google ScholarCross Ref
- Robert K Merton. 1988. The Matthew effect in science, II: Cumulative advantage and the symbolism of intellectual property. Isis (1988), 606–623.Google Scholar
- Márton Mestyán, Taha Yasseri, and János Kertész. 2013. Early prediction of movie box office success based on Wikipedia activity big data. PloS one 8, 8 (2013), e71226.Google ScholarCross Ref
- Shuyo Nakatani. 2010. Language Detection Library for Java. (2010). http://code.google.com/p/language-detection/Google Scholar
- Oded Nov, Mor Naaman, and Chen Ye. 2008. What drives content tagging: the case of photos on Flickr. In Proceedings of the SIGCHI conference on Human factors in computing systems. ACM, 1097–1100. Google ScholarDigital Library
- Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, and others. 2011. Scikit-learn: Machine learning in Python. The Journal of Machine Learning Research 12 (2011), 2825–2830. Google ScholarDigital Library
- Alexander Michael Petersen, Santo Fortunato, Raj K. Pan, Kimmo Kaski, Orion Penner, Armando Rungi, Massimo Riccaboni, H. Eugene Stanley, and Fabio Pammolli. 2014. Reputation and impact in academic careers. Proceedings of the National Academy of Sciences 111, 43 (2014), 15316–15321.Google ScholarCross Ref
- Matthew J. Salganik, Peter Sheridan Dodds, and Duncan J. Watts. 2006. Experimental Study of Inequality and Unpredictability in an Artficial Cultural Market. Science 311, 5762 (2006), 854–856.Google Scholar
- Matthew Schneier. 2014. Fashion in the Age of Instagram. (April 2014). http://www.nytimes.com/2014/04/10/fashion/ fashion-in-the-age-of-instagram.html?_r=0 {Online; posted 9-April-2014}.Google Scholar
- Arnout van de Rijt, Soong Moon Kang, Michael Restivo, and Akshay Patil. 2014. Field experiments of success-breeds-success dynamics. Proceedings of the National Academy of Sciences 111, 19 (2014), 6934–6939.Google ScholarCross Ref
- Yiran Wang, Melissa Niiya, Gloria Mark, Stephanie M. Reich, and Mark Warschauer. 2015. Coming of Age (Digitally): An Ecological View of Social Media Use Among College Students. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW '15). ACM, New York, NY, USA, 571–582. Google ScholarDigital Library
- Alexandra Weilenmann, Thomas Hillman, and Beata Jungselius. 2013. Instagram at the museum: communicating the museum experience through social photo sharing. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1843–1852. Google ScholarDigital Library
- Wikipedia. 2014. Fashion Model Directory. (2014). http://en.wikipedia.org/w/index.php?title= Fashion_Model_Directory {Online; accessed 20-April-2015}.Google Scholar
- Elizabeth Wissinger. 2009. Modeling Consumption: Fashion modeling work in contemporary society. Journal of consumer culture 9, 2 (2009), 273–296.Google ScholarCross Ref
- Kate Zernike. 2004. Sizing Up America: Signs of Expansion From Head to Toe. (March 2004). http://goo.gl/E8I8Co {Online; posted 1-March–2004}.Google Scholar
Recommendations
Gratifications of using Facebook, Twitter, Instagram, or Snapchat to follow brands
Snapchat is used for passing time, sharing problems, and social knowledge.Instagram is used for showing affection, following fashion, and sociability.Twitter users had highest brand community identification and membership intention.Instagram users had ...
Design and Development of Intelligent Decision Support Prototype System for Social Media Competitive Analysis in Fashion Industry
This paper describes the design and development of an intelligent decision support system IDSS for competitive analysis of social media in the fashion industry. A web-based prototype system is designed and developed to assist in monitoring the growing ...
Comments