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English(EN) Beyond the Black Box: Integrating Lexical and Semantic Methods in Quantitative Discourse Analysis with BERTopic

新框架整合词汇和语义方法用于话语分析

作者 PulseAugur 编辑部 · [1 个来源] ·

一篇研究论文提出了一种用于定量话语分析的混合框架，该框架整合了词汇和语义方法。该方法旨在通过结合自定义Python管道与NLTK、spaCy、Sentence Transformers和BERTopic等工具，提高计算话语研究的透明度、可复现性和可解释性。论文详细介绍了迭代BERTopic建模过程，包括UMAP、HDBSCAN和c-TF-IDF，以提高主题连贯性和覆盖率，并提供了一种多层次的策略来克服孤立方法的局限性。 AI

影响 提高了计算话语分析的透明度和可复现性，可能影响研究人员如何利用LLMs进行文本分析。

排序理由 研究论文，详细介绍了一种新的话语分析方法。 [lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新框架整合词汇和语义方法用于话语分析

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研究论文，详细介绍了一种新的话语分析方法。 [lever_c_demoted from research: ic=1 ai=0.7]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Thomas Compton ·

    Beyond the Black Box: Integrating Lexical and Semantic Methods in Quantitative Discourse Analysis with BERTopic

    arXiv:2508.19099v2 Announce Type: replace Abstract: Quantitative Discourse Analysis has seen growing adoption with the rise of Large Language Models and computational tools. However, reliance on black box software such as MAXQDA and NVivo risks undermining methodological transpar…

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