开源文本分析工具，助社会科学家可视化研究文化模式。
The Cultural Mapping and Pattern Analysis (CMAP) Visualization Toolkit: Open Source Text Analysis for Qualitative and Computational Social Science
- 基于研究目标设计的可调参数工具，适配多种社会科学研究范式。
- 支持从访谈记录到网络数据的大规模文本分析与可视化。
- 兼容Python生态，适合需要灵活分析的社会科学学者。
本文介绍的CMAP（文化映射与模式分析）可视化工具包是一个开源套件，用于分析和可视化文本数据，涵盖定性田野笔记、深度访谈转录稿、历史文献及网络抓取数据（如留言板帖子或博客）。该工具包专为整合模式分析、数据可视化与解释的定性与/或计算社会科学研究（CSS）设计。尽管已有商用定性数据分析软件，但缺乏能处理大规模数据集并支持高级统计与语言建模的开源选项。工具包的核心理念是将研究工具与社会科学研究目标（如经验解释、理论引导的测量、比较设计或证据基础建议）对齐，遵循研究范式与问题决定方法的原则。因此，通过少量参数调整，CMAP提供多样化可能性，并可与其它Python工具集成。
原文摘要 · Abstract (English)
The CMAP (cultural mapping and pattern analysis) visualization toolkit introduced in this paper is an open-source suite for analyzing and visualizing text data - from qualitative fieldnotes and in-depth interview transcripts to historical documents and web-scaped data like message board posts or blogs. The toolkit is designed for scholars integrating pattern analysis, data visualization, and explanation in qualitative and/or computational social science (CSS). Despite the existence of off-the-shelf commercial qualitative data analysis software, there is a dearth of highly scalable open source options that can work with large data sets, and allow advanced statistical and language modeling. The foundation of the toolkit is a pragmatic approach that aligns research tools with social science project goals- empirical explanation, theory-guided measurement, comparative design, or evidence-based recommendations- guided by the principle that research paradigm and questions should determine methods. Consequently, the CMAP visualization toolkit offers a range of possibilities through the adjustment of relatively small number of parameters, and allows integration with other python tools.
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