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Dataset Description.

Dataset Description.

Source publication
Conference Paper
Full-text available
Esports, like traditional sports, face governance challenges such as foul play and match fixing. The esports industry has seen various attempts at governance structure but is yet to form a consensus. In this study, we explore esports governance in League of Legends (LoL), a major esports title. Through a two-stage, mixed-methods analysis of rule en...

Contexts in source publication

Context 1
... identified four primary categories of penalties, as described in Table 1, including warning, fine, community service, and competition ban. Knowledge accumulated in the content analysis processes informed us of the presence of severity of penalty in Riot's rule enforcement decisions. ...
Context 2
... procedure developed the category of competition ban into competition ban in (0, 1 month), competition ban in [1 month, one year), competition ban in [1 year, two years), competition ban in [2 years, + ∞). The content analysis led to 11 categories of ruling-breaking behaviors and an eight-level punishment hierarchy (see Table 1 for details). ...
Context 3
... second stage of this study aimed to answer the second research question, how contextual factors influence rule enforcement. We completed several data preprocessing steps and developed a dataset for quantitative analysis, as shown in Table 1. We ran both Cramer's V (Φc) and Pearson's correlation on the dataset to uncover the relationship between contextual factors and governance outcomes. ...
Context 4
... we assumed daily currency movement was not a considerable factor in this study. Forth, we used binary encoding to represent ruling cases with or without a fine between 1 and 0. Finally, we added the region variable by combining relevant game servers in Riot's institutional structure, resulting in 12 regions, as shown in Table 1. ...
Context 5
... identified four primary categories of penalties, as described in Table 1, including warning, fine, community service, and competition ban. Knowledge accumulated in the content analysis processes informed us of the presence of severity of penalty in Riot's rule enforcement decisions. ...
Context 6
... procedure developed the category of competition ban into competition ban in (0, 1 month), competition ban in [1 month, one year), competition ban in [1 year, two years), competition ban in [2 years, + ∞). The content analysis led to 11 categories of ruling-breaking behaviors and an eight-level punishment hierarchy (see Table 1 for details). ...
Context 7
... second stage of this study aimed to answer the second research question, how contextual factors influence rule enforcement. We completed several data preprocessing steps and developed a dataset for quantitative analysis, as shown in Table 1. We ran both Cramer's V (Φc) and Pearson's correlation on the dataset to uncover the relationship between contextual factors and governance outcomes. ...
Context 8
... movement was not a considerable factor in this study. Forth, we used binary encoding to represent ruling cases with or without a fine between 1 and 0. Finally, we added the region variable by combining relevant game servers in Riot's institutional structure, resulting in 12 regions, as shown in Table 1. ...