A Study on the Perception and Context of Sportswear Brand Collaboration through Big Data Analysis

Recently, brand collaboration is attracting the attention of the industry as one of the strategies for brand differentiation. It is a marketing activity in which two or more brands of the same kind or different kinds create new brands together to target consumers, and it has developed into a form of productive collaboration that combines and creates new values beyond the level of mutual complementation between individual brands, and is being attempted in many fields. The sportswear industry is also recovering as it has passed the COVID-19 pandemic and has shifted to endemics. This study is to understand consumers' perceptions of sports collaboration brands on social media and provide basic data to related industries. Social media channels are Naver and Google sites. Naver channels collected data from blogs and news sections, Google channels collected data from news and Facebook sections, and used Textom version 6.0, a big data analysis solution, for data collection. The collection period was collected from May 11, 2023, during the transition from the COVID-19 pandemic to the end of the pandemic, to June 30, 2024. The collected data are 2,667 blogs and 761 news on Naver channels. They are 222 news and 41 Facebook on Google channels. The collected data was converted into standardized data through preprocessing. TF and TF-IDF were analyzed through text mining. Sixty keywords were extracted in consideration of the frequency of keywords and the importance in the sentence. Semantic matrix and Concore analysis were performed on the extracted keywords. Big data analysis programs such as Textom and Ucinet were used for big data analysis, and NetDraw was used for visualization. As a result of text mining analysis, 'collaboration' showed the highest frequency with 4,860 times in relation to TF. Next, brand(3,835), sports(1,934), product(1,442), 'X'(1,125), global(1,116), release(1,064), and Nike(937), were shown in the highest order. In terms of TF-IDF, 'Nike' was the highest at 2153. Next, Puma(1,996), product(1,731), 'X'(1,659), collection(1,516), Golf(1,494), and release(1,476) were found to be high. As a result, 60 keywords were extracted and the centrality was analyzed through semantic matrix analysis. Finally, through CONCOR analysis, they were clustered into marketing strategy cluster, 'sports brand cluster', 'recommendation cluster', and 'Nike cluster'. For the results of these four cluster analysis, basic practical data were presented based on the main interest, perception, and context of 'sports brand collaboration' of consumers.