Abstract
In this era of big data, even though there exists an abundance of data documenting fashion and fashion trends, there has barely been any quantitative research conducted on the topic of influence or leadership. Unlike many other innovation domains such as patents where citations are explicit, a fashion designer hardly claims that s/he is influenced by others. To trace the hidden fashion influence network, we propose a novel approach to analyze the design influence in fashion industry by comparing similarity between designers in adopting same fashion symbols. Based on text processing techniques, we develop a quantitative model to extract fashion influences from 14-year historical data on fashion reviews. A total of 6,629 fashion runway reviews from the year 2000 to 2014 have been collected for analysis. We compared the performance of our proposed model with the globally published "most influential" lists and calculated a performance of 92.81% area under curve (AUC).
| Original language | English (US) |
|---|---|
| Title of host publication | 24th Workshop on Information Technology and Systems |
| Publisher | University of Auckland Business School |
| State | Published - 2014 |
| Event | 24th Annual Workshop on Information Technologies and Systems: Value Creation from Innovative Technologies, WITS 2014 - Auckland, New Zealand Duration: Dec 17 2014 → Dec 19 2014 |
Other
| Other | 24th Annual Workshop on Information Technologies and Systems: Value Creation from Innovative Technologies, WITS 2014 |
|---|---|
| Country/Territory | New Zealand |
| City | Auckland |
| Period | 12/17/14 → 12/19/14 |
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Information Systems
- Computer Science Applications