2019 年に大阪大学出版会から刊行した『探索的コーパス言語学：データ主導の日本語研究・試論』の中核部分の英訳版。「データによってデータそのものを説明する」方式による新しいコーパス言語学を標榜し、日本語研究の新たな可能性について事例的研究と方法論的検討をもとに論じる。研究成果を英語で発表した書籍はまだ出版されておらず、多言語圏においても広く参照応用されうる先駆的な学術書。
Preface

CHAPTER 1 What is exploratory corpus linguistics?
1. Introduction
2. Large-scale corpus linguistics
3. Methodological developments in statistical studies
4. Methodological developments in corpus linguistics studies
5. The current state of Japanese corpus linguistics
6. Issues in exploratory corpus linguistics

PART 1. Exploration using full-text corpora

CHAPTER 2 Text mechanisms for the generation of low-frequency words
1. Problem proposal
2. Methodology
3. Evaluation of the validity of the problem proposal and methodology
4. Issues

CHAPTER 3 In-text formation of nonce four-character compound words
1. Introduction
2. Nonce word formation and text
3. Text-manifested nonce word formation
4. In demonstrative phrases
5. Recapturing or repeating?
6. Syntactic repositioning patterns
7. Toward an elucidation of mechanisms based in text theory

CHAPTER 4 Defure kara dakkyaku suru:Collocation establishment and change in newspapers
1. Introduction
2. Research methods for collocation change
3. Subjects and materials: “Defure ＋ verb” phrases in newspapers
4. The level of describing meaning: Collocation establishment
5. The level of indicating reality: Collocation change
6. Summary and future issues

PART 2. Exploration using various corpora

CHAPTER 5 The potential for Japanese language research using various corpora
1. Introduction
2. Multilevel diachronic corpus
3. Monolingual parallel corpus
4. Multimedia corpora
5. Discourse corpus
6. Problems with large-scale corpora
7. Conclusion

PART 3. Exploration through exploratory data analysis

CHAPTER 6 Japanese language research through exploratory data analysis
1. Introduction
2. The NINJAL Vocabulary Survey of Television Broadcasts
3. Using the highly resistant median as a measure of central tendency
4. Exploring distribution shapes using stem-and-leaf plots
5. Visually outlining distributions using box plots
6. Finding and examining outliers
7. Smoothing time-series data and exploring patterns of change
8. Exploring relationships between two variables with resistant lines
9. Exploring factor effects with two-way analysis
10. Comparing two groups with ridit analysis
11. Comparing proportion change using re-expression　(logit transformation)
12. Conclusion

CHAPTER 7 Discovering S-curves using wandering box plots
1. Introduction
2. Exploratory data analysis
3. Summary of Yasumoto (1963) and its problems
4. Summary of Kinsui (2004) and its problems
5. Wandering box plots
6. Wandering box plots of the Yasumoto data
7. Wandering box plots of the Kinsui data
8. Conclusion

CHAPTER 8 Analysis of count data using ridit analysis
1. Introduction
2. Philosophy and methods of ridit analysis
3. Intergroup comparison of qualitative data
4. Intergroup comparison of quantitative data
5. Quantifying bivariate ordered categories
6. Conclusion

References