Using quantitative approaches to investigate complicated linguistic phenomena has long been a research focus in natural language processing (NLP), serving a variety of disciplines, such as quantitative linguistics, corpus linguistics, and computational linguistics. Particularly, the rise of data analytics and computational social science in the past decade has changed the nature of available quantitative analysis tools. Researchers wishing to facilitate their tasks with such new tools are offered more opportunities and favorable conditions to seek convincing empirical evidence for defending their argument. In this respect, Díaz and López’s book entitled Negation and Speculation Detection in the John Benjamins Natural Language Processing series appears to be a timely and popular contribution because it elucidates for readers a wide range of practical application of data analytic measures to look at negation and speculation, breaking the constraints of examining these two expressive phenomena merely from a theoretical perspective. The potential readership for the volume covers a broad spectrum, which may include NLP researchers, quantitative linguists, university teachers, students of postgraduate levels, and anyone who shows an interest in quantitative studies.

中文翻译：

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否定和推测检测。Noa P. CruzDíaz和Manuel J.MañaLópez。阿姆斯特丹/费城：约翰·本杰明斯（John Benjamins），2019年.ix + 95页，ISBN 978-90-272-0217-8。€95.00（精装本）。

长期以来，使用定量方法来研究复杂的语言现象一直是自然语言处理（NLP）的研究重点，服务于多种学科，例如定量语言学，语料库语言学和计算语言学。特别是，过去十年中数据分析和计算社会科学的兴起改变了可用定量分析工具的性质。希望通过这种新工具来完成任务的研究人员获得了更多机会和有利条件，以寻求有说服力的经验证据来捍卫他们的论点。在这方面，Díaz和López的书名为《约翰·本杰明斯自然语言处理中的否定和推测检测》该系列似乎是及时而流行的贡献，因为它向读者阐明了数据分析手段在否定和推测方面的广泛实际应用，仅从理论角度打破了检查这两种表现现象的限制。该卷的潜在读者覆盖广泛，其中可能包括NLP研究人员，定量语言学家，大学教师，研究生水平的学生以及对定量研究感兴趣的任何人。