通过望远镜结晶化模式：对Reddit大型文本语料的主题整理
Crystallizing Schemas with Teleoscope: Thematic Curation of Large Text Corpora on Reddit
AI总结：
本文提出Teleoscope系统，通过主题整理方法提升对Reddit大型文本语料的分析效率，支持意外发现新关键词，增强搜索饱和感，并促进协作讨论。
摘要：
大型文本语料，如Reddit帖子，已成为质性研究日益普遍的场所。然而，大多数大型文本语料对质性研究者来说难以处理。相反，团队依赖统计抽样来减少语料库到可管理的大小进行质性分析。尽管先前的工作涉及在语料库层面可视化数据集使用高级统计摘要，但很少有系统能提供基于解释主义方法的数据整理能力。为此，我们开发了Teleoscope，一个基于网页的界面，旨在构建迭代、互动和反思性细化大型语料库的过程，称为主题整理。在三次部署中，我们发现Teleoscope支持意外发现新关键词，导致更大的搜索饱和感信心，并帮助协作讨论替代整理路径。Teleoscope使研究者能够保持'贴近数据'，以使质性工作流程与大型文本语料库在方法上一致。
英文摘要：
Large text corpora, such as Reddit posts, have become an increasingly prevalent site of qualitative inquiry. However, most large text corpora are intractable for qualitative researchers. Instead, teams rely on statistical subsampling to reduce corpora to a manageable size for qualitative analysis. While previous work for navigating large corpora involves visualizing the dataset at the corpus-level using high-level statistical summaries, few systems offer the ability to curate data using an interpretivist approach. To address this, we developed Teleoscope, a web-based interface designed to scaffold iterative, interactive, and reflexive refinement of a large corpus, in a process we call thematic curation. Across three deployments, we learned that Teleoscope supports serendipitous discovery of new keywords, results in greater feelings of confidence in search saturation, and aids collaborative discussion of alternative curation pathways. Teleoscope empowers researchers to stay "close to the data" in order to make qualitative workflows methodologically coherent with large text corpora.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
