Data visualization practitioners routinely invoke inspiration, yet we know little about how it is constructed in public conversations. We conduct a discourse analysis of 31 episodes from five popular data visualization podcasts. Podcasts are public-facing and inherently performative: guests manage impressions, articulate values, and model "good practice" for broad audiences. We use this performative setting to examine how legitimacy, identity, and practice are negotiated in community talk. We show that "inspiration talk" is operative rather than ornamental: speakers legitimize what counts, who counts, and how work proceeds. Our analysis surfaces four adjustable evaluation criteria by which inspiration is judged-novelty, authority, authenticity, and affect-and three operative metaphors that license different practices-spark, muscle, and resource bank. We argue that treating inspiration as a boundary object helps explain why these frames coexist across contexts. Findings provide a vocabulary for examining how inspiration is mobilized in visualization practice, with implications for evaluation, pedagogy, and the design of galleries and repositories that surface inspirational examples.

翻译：数据可视化从业者经常提及灵感，但我们对其在公共对话中的建构机制知之甚少。本研究对五个热门数据可视化播客的31期节目进行了话语分析。播客面向公众且具有天然的表演性：嘉宾通过印象管理、价值阐述以及为广泛受众示范"良好实践"来塑造专业形象。我们利用这一表演性场景，考察了社群对话中合法性、身份认同与实践方式是如何被协商的。研究表明，"灵感对话"具有操作性而非装饰性：发言者通过话语确立何为重要、谁值得关注以及工作应如何推进。我们的分析揭示了评判灵感的四个可调节标准——新颖性、权威性、真实性与情感共鸣，以及授权不同实践方式的三个操作隐喻——火花、肌肉与资源库。我们认为将灵感视为边界对象有助于解释这些框架为何能在不同语境中共存。研究结果为审视灵感在可视化实践中的动员机制提供了概念工具，对评估体系、教学方法以及展示灵感案例的画廊与资源库设计具有启示意义。