衡量基于游戏的社区对女性的毒性

Matthew Belskie, Hanlin Zhang, B. Hemminger
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摘要

之前针对特定游戏Reddit社区的游戏毒性研究几乎总是考虑到整体的毒性,因此对于隔离有毒语言和专门针对女性玩家的触发器的有效编码方案提供的线索很少。现有的研究为设计有效的方法来测量和检测特定数据集中的有毒语言和有毒诱因提供了一个起点,但这些研究在针对女性玩家的与游戏相关的有毒形式的适用性方面用处不大。该研究最初希望开发一种自动评分方法,但文中讨论的毒性自动检测的局限性促使作者将其转变为关键的中间步骤——通过自动化手段提高毒性检测的准确性——这将有助于未来在减少对女性和游戏社区中其他目标群体的毒性方面取得成就。本文旨在帮助我们更好地理解游戏和游戏社区对女性的负面影响,以及如何有效地衡量这种影响。这项研究的结论最终希望能够为政策提供信息,为所有玩家创造一个更安全、更受尊重的游戏环境。
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Measuring Toxicity Toward Women in Game-Based Communities
Prior research into gaming toxicity in game-specific Reddit communities nearly always considers toxicity in aggregate, and so provides very few clues for a valid coding scheme for isolating toxic language and triggers that specifically target women gamers. Existing research offers a starting place for devising valid methods for measuring and detecting toxic language and toxic triggers within specified data sets, but that research is less useful is its applicability to game-related forms of toxicity targeting women gamers. Where this research had originally hoped to develop an automated method for scoring, limitations with automated detection of toxicity discussed within the paper prompted a shift to what the authors identify as a key intermediate step—better accuracy in toxicity detection by automated means—that will contribute to future achievements in reducing toxicity toward women and other targeted groups in gaming communities. This paper is intended to aid projects that aim to incrementally improve our understanding of toxicity toward women in games and game communities and how to effectively measure it. The conclusion of this research ultimately hopes to contribute to providing information to inform policies that create a safer and more respectful gaming environment for all gamers.
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