Big Data and Innovative Research Methods

被引:5
|
作者
Mamo, Yoseph Z. [1 ]
机构
[1] Old Dominion Univ, Dept Human Movement Sci, Sport Management, Norfolk, VA 23529 USA
关键词
sentiment analysis; machine learning; natural language processing; sport management; social media; GAMES;
D O I
10.1123/ijsc.2023-0109
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
Big data and innovative research methods are two rapidly evolving trends that are transforming how we conduct research in sport management. Considering the natural relationship between social media, which is widely recognized as a major big-data source, and sport, this commentary centers on contemporary research method applied to social media data. In doing so, it discusses contemporary innovative techniques for social media data, focusing on exploring ways to access social media data, the natural language-processing techniques used, the challenges they address, the strengths and limitations of different techniques, and the ethical and privacy considerations associated with their use. Furthermore, the commentary demonstrates that using sentiment analysis tools (e.g., Syuzhet, Bing, and AFFIN) is appropriate and efficient in analyzing sport's social media data. Thus, a rigorous application of contemporary innovative techniques can significantly shape the future of sport management research. However, researchers must exercise caution when considering the source and preprocessing of the data prior to applying advanced analytical techniques.
引用
收藏
页码:352 / 360
页数:9
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