Name
Abstract | ||
|---|---|---|
The advent of social media has allowed channeling of the voice of sports fans that have essentially lead to gathering and storing fan-generated, large-scale opinions about sports match and team performance. Although research utilizing social media data for the purposes of supporting consumer market research has been increasing throughout the recent decade, there is a lack of studies using social media mining approach to improve team performance. In this paper, an opportunity mining approach is proposed to identify opportunities to improve team performance based on text mining and cluster analysis. A case study of the 2018 Federation Internationale de Football Association (FIFA) World Cup final qualification of Korea, Korea versus Uzbekistan, was conducted to explain how the proposed method works. Fan comment data collected in the study revealed 16 different opportunities that would satisfy fans with regard to the team performance, and of those, two main extreme opportunities were identified. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACCESS.2019.2912009 | IEEE ACCESS |
Keywords | Field | DocType |
Text-mining,clustering methods,opportunity algorithm,social network services | Data science,Football,Social media,Social media mining,Computer science,Computer network,Wisdom of crowds,Consumer market | Journal |
Volume | ISSN | Citations |
7 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seok Young Kim | 1 | 2 | 2.38 |
| Mijung Kim | 2 | 0 | 0.34 |