Multiplayer Online Battle Arenas (MOBAs) have gained a significant player base worldwide, generating over two billion US dollars in annual game revenue. However, the presence of griefers, who deliberately irritate and harass other players within the game, can have a detrimental impact on players' experience, compromising game fairness and potentially leading to the emergence of gray industries. Unfortunately, the absence of a standardized criterion, and the lack of high-quality labeled and annotated data has made it challenging to detect the presence of griefers. Given the complexity of the multivariant spatiotemporal data for MOBA games, game developers heavily rely on manual review of entire game video recordings to label and annotate griefers, which is a time-consuming process. To alleviate this issue, we have collaborated with a team of game specialists to develop an interactive visual analysis interface, called GrieferLens. It overviews players' behavior analysis and synthesizes their key match events. By presenting multiple views of information, GrieferLens can help the game design team efficiently recognize and label griefers in MOBA games and build up a foundation for creating a more enjoyable and fair gameplay environment.

翻译：多人在线战术竞技游戏（MOBA）在全球范围内积累了庞大的玩家群体，年收入超过20亿美元。然而，游戏中故意激怒和骚扰其他玩家的消极玩家（griefer）会严重影响游戏体验，破坏游戏公平性，甚至催生灰色产业。由于缺乏标准化判定标准以及高质量标注数据，检测消极玩家存在较大困难。考虑到MOBA游戏中多维时空数据的复杂性，游戏开发者主要依赖人工回放完整游戏录像来标记消极玩家，这一过程耗时巨大。为解决此问题，我们与游戏专家团队合作开发了名为GrieferLens的交互式可视化分析界面。该系统通过全局玩家行为分析并整合关键比赛事件，利用多视图信息展示，帮助游戏设计团队高效识别和标注MOBA游戏中的消极玩家，为构建更愉悦公平的游戏环境奠定基础。