366029858 03 01 01 JB John Benjamins Publishing Company 01 JB code SCL 118 Eb 15 9789027246530 06 10.1075/scl.118 13 2024029609 DG 002 02 01 SCL 02 1388-0373 Studies in Corpus Linguistics 118 01 scl.118 01 https://benjamins.com 02 https://benjamins.com/catalog/scl.118 1 B01 Mark Kaunisto Kaunisto, Mark Mark Kaunisto Tampere University 2 B01 Marco Schilk Schilk, Marco Marco Schilk University of Hildesheim 01 eng 180 vii 172 LAN009000 v.2006 CFX 2 24 JB Subject Scheme LIN.APPL Applied linguistics 24 JB Subject Scheme LIN.COMPUT Computational & corpus linguistics 24 JB Subject Scheme LIN.CORP Corpus linguistics 24 JB Subject Scheme LIN.THEOR Theoretical linguistics 06 01 This book contributes to the discussion of challenges faced in different areas of corpus linguistics, namely the compilation, annotation, and analysis of linguistic corpora. In a field of growing corpus sizes and expanding possibilities of gathering data, some old issues persist, while at the same time new problems have emerged. As the compilation and study of language corpora gets increasingly sophisticated and complex, continuous attention on ways of dealing with the data in question and challenges in text selection and interpretation is needed. The contributions to this volume address problems relating to a variety of areas in corpus linguistic study, including corpus annotation, data variability, learner language, social media texts, and database utilization. The authors provide critical overviews and research-based analyses, discuss the nature of some of the common pitfalls, and offer solutions to existing problems. 04 09 01 https://benjamins.com/covers/475/scl.118.png 04 03 01 https://benjamins.com/covers/475_jpg/9789027215888.jpg 04 03 01 https://benjamins.com/covers/475_tif/9789027215888.tif 06 09 01 https://benjamins.com/covers/1200_front/scl.118.hb.png 07 09 01 https://benjamins.com/covers/125/scl.118.png 25 09 01 https://benjamins.com/covers/1200_back/scl.118.hb.png 27 09 01 https://benjamins.com/covers/3d_web/scl.118.hb.png 10 01 JB code scl.118.toc v vi 2 Miscellaneous 1 10 01 JB code scl.118.ack vii viii 2 Miscellaneous 2 10 01 JB code scl.118.01kau 1 8 8 Chapter 3 1 A01 Mark Kaunisto Kaunisto, Mark Mark Kaunisto Tampere University 10 01 JB code scl.118.02var 9 34 26 Chapter 4 1 A01 Turo Vartiainen Vartiainen, Turo Turo Vartiainen University of Helsinki 2 A01 Tanja Säily Säily, Tanja Tanja Säily University of Helsinki 20 big data 20 corpus compilation 20 historical corpus linguistics 20 metadata 20 part-of-speech annotation 20 sampling 01 In this chapter, we discuss some common pitfalls related to historical data and its use in linguistic analysis. We argue that the “philologist’s dilemma”, as originally proposed by Rissanen (1989), should be reconceptualized to meet the needs of the fast-evolving field of corpus linguistics, where scholars make increasing use of big-data resources and sophisticated statistical modelling. By providing examples of errors and uncertainties related to, for example, corpus metadata, sampling, balance, and OCR accuracy, we argue that corpus linguists should pay increasingly close attention to the sampling and annotation principles employed in the compilation of historical corpora as well as to the quality of the linguistic data. We propose that the principle of “knowing one’s corpus” in terms of its compilation principles has become all the more important in the age of big-data corpora, where it is not feasible for individual researchers, or corpus compilers, to validate their data manually. 10 01 JB code scl.118.03kau 35 54 20 Chapter 5 1 A01 Mark Kaunisto Kaunisto, Mark Mark Kaunisto Tampere University 20 annotation 20 corpus linguistics 20 named entities 20 proper names 01 This chapter discusses problems in the interpretation of corpus data arising from the insufficiencies in the annotation of named entities. Many corpora nowadays still do not adequately enable corpus users to set up queries that would exclude items appearing in names when needed to improve precision of the searches. Through an examination of case studies in major English language corpora, the chapter highlights the need to carefully post-process the search results, as irrelevant occurrences of named entities may pose challenges in the analyses of word frequencies and their collocational behaviour. The chapter calls for more detailed annotation of named entities in already available large linguistic corpora and reminds of the importance of close inspection of the search hits. 10 01 JB code scl.118.04cal 55 67 13 Chapter 6 1 A01 Marcus Callies Callies, Marcus Marcus Callies University of Bremen 20 analysis 20 annotation 20 compilation 20 discourse of deficit 20 learner corpus 20 lexical bias 20 lexical innovation 20 multilingualism 20 task instruction 20 writing prompt 01 This chapter highlights and discusses the special characteristics of learner corpus data and the challenges they may present for corpus compilation, annotation, and analysis. Because learner corpus and SLA researchers use their data to study L2 production and development, it is of utmost importance that the data are valid, that is, they represent “authentic” L2 production, which means that the data must stem from the studied learners’ own language production. I discuss challenges in three areas: (1) multilingual practices and metalinguistic language use, (2) lexical and constructional bias, often brought about by the wording of task instructions or writing prompts that learners are asked to respond to, and (3) learner corpus annotation in view of the “discourse of deficit” in SLA. For each of these challenges solutions as to how they can be met are offered. 10 01 JB code scl.118.05hil 68 88 21 Chapter 7 1 A01 Turo Hiltunen Hiltunen, Turo Turo Hiltunen University of Helsinki 20 corpus compilation 20 Digital Humanities 20 register 20 representativeness 20 sampling 01 The availability of large digital archives has great potential for corpus linguistic research, but their use is not without problems. These problems can often be traced to fundamentally different ideas of what might constitute “good data” in Digital Humanities and in corpus linguistics, leading to different expectations regarding how the data is made available to researchers. This chapter discusses the specific challenges involved in using the <i>British Library Newspapers</i> database for corpus linguistics and considers potential solutions for them. It is argued that, to take full advantage of the database, it is necessary to adopt a flexible approach enabling a critical reflection on the digital materials, how they have been collected, processed, and made available. 10 01 JB code scl.118.06har 89 105 17 Chapter 8 1 A01 Stefan Hartmann Hartmann, Stefan Stefan Hartmann Heinrich Heine University Düsseldorf 20 accessibility 20 open research 20 replicability 20 representativeness 20 transparency 01 In recent years, many researchers have called attention to the fact that research results very often cannot be replicated – a phenomenon that has been called <i>replication crisis</i>. The replication crisis in linguistics is highly relevant to corpus-based research: Many corpus studies are not directly replicable as the data on which they are based are not readily available. Especially in English linguistics, the full versions of many widely used corpora are still behind paywalls, which means that they are not accessible to parts of the global research community, and even when parts of the data are freely accessible, this presents problems for state-of-the-art methods of data analysis. In this paper, I discuss the challenges that have led to this situation and address some possible solutions. In particular, I argue for using smaller but openly available corpora whenever possible and for adopting open research practices as far as possible even when using commercial corpora. 10 01 JB code scl.118.07lii 106 125 20 Chapter 9 1 A01 Aatu Liimatta Liimatta, Aatu Aatu Liimatta University of Helsinki 20 lengthwise analysis 20 lexical diversity 20 normalization 20 text length 01 Variation in text length is an unavoidable confounder in quantitative text-analytic corpus-linguistic studies. Texts can be difficult to compare across text lengths, particularly if many of them are short, due to the difficulty of calculating meaningful frequencies for the lexical items and linguistic features of interest. Traditionally, this has been less of an issue, since texts in many of the genres typically studied in linguistics have been relatively long. However, the rise of social media has brought the issue to the forefront. In this chapter, I describe the problem of text length and short texts together with a number of solutions and workarounds to this and related problems. 10 01 JB code scl.118.08ihr 126 141 16 Chapter 10 1 A01 Daniel Ocic Ihrmark Ihrmark, Daniel Ocic Daniel Ocic Ihrmark Linnaeus University 20 corpus linguistics 20 genre 20 literature 20 special corpora 20 stylistics 01 This chapter highlights genre categorizations as a pitfall at the intersection of corpus linguistics and literature and problematizes the use of the genre category from the perspectives afforded by both fields. The intention is for the paper to argue for a more explicit communication of our genre categorization practices, and by doing so suggest ways of avoiding miscommunication and confusion due to the genre term being understood differently within different disciplines and backgrounds. The conclusion is that the wider categorizations used, such as <i>novel</i> or <i>short story</i>, are likely to be the most practical, and that studies wanting to sub-categorize further using the genre term should instead apply it according to their specific needs accompanied by explicit discussion of the implementation. 10 01 JB code scl.118.09mil 142 170 29 Chapter 11 1 A01 Filip Miletic Miletic, Filip Filip Miletic CLLE, CNRS & University of Toulouse | IMS, University of Stuttgart 2 A01 Anne Przewozny-Desriaux Przewozny-Desriaux, Anne Anne Przewozny-Desriaux CLLE, CNRS & University of Toulouse 3 A01 Ludovic Tanguy Tanguy, Ludovic Ludovic Tanguy CLLE, CNRS & University of Toulouse 20 language contact 20 large language models 20 Quebec English 20 semantic shifts 20 Twitter corpora 20 word embeddings 01 This chapter examines the use of recent data sources and computational methods to study fine-grained sociolinguistic phenomena. We deploy a custom-built corpus of tweets (Miletić et al. 2020) and neural word embeddings to investigate the use of contact-induced semantic shifts in Quebec English. Drawing on an analysis of 40 lexical items, we show that our approach is beneficial in facilitating manual inspection of vast amounts of data and establishing fine-grained patterns of language variation. While it is affected by a range of noise-related issues, which we describe in detail, coarse-grained annotation provides an efficient way of circumventing them. We use the results filtered in this way to conduct a quantitative analysis of sociolinguistic constraints on contact-induced semantic shifts, further confirming the relevance of our approach. 10 01 JB code scl.118.si 171 172 2 Miscellaneous 12 02 JBENJAMINS John Benjamins Publishing Company 01 John Benjamins Publishing Company Amsterdam/Philadelphia NL 02 September 2024 20240915 2024 John Benjamins B.V. 02 WORLD 13 15 9789027215888 01 JB 3 John Benjamins e-Platform 03 jbe-platform.com 09 WORLD 21 20240915 01 00 115.00 EUR R 01 00 97.00 GBP Z 01 gen 00 149.00 USD S 906029857 03 01 01 JB John Benjamins Publishing Company 01 JB code SCL 118 Hb 15 9789027215888 13 2024029608 BB 01 SCL 02 1388-0373 Studies in Corpus Linguistics 118 01 scl.118 01 https://benjamins.com 02 https://benjamins.com/catalog/scl.118 1 B01 Mark Kaunisto Kaunisto, Mark Mark Kaunisto Tampere University 2 B01 Marco Schilk Schilk, Marco Marco Schilk University of Hildesheim 01 eng 180 vii 172 LAN009000 v.2006 CFX 2 24 JB Subject Scheme LIN.APPL Applied linguistics 24 JB Subject Scheme LIN.COMPUT Computational & corpus linguistics 24 JB Subject Scheme LIN.CORP Corpus linguistics 24 JB Subject Scheme LIN.THEOR Theoretical linguistics 06 01 This book contributes to the discussion of challenges faced in different areas of corpus linguistics, namely the compilation, annotation, and analysis of linguistic corpora. In a field of growing corpus sizes and expanding possibilities of gathering data, some old issues persist, while at the same time new problems have emerged. As the compilation and study of language corpora gets increasingly sophisticated and complex, continuous attention on ways of dealing with the data in question and challenges in text selection and interpretation is needed. The contributions to this volume address problems relating to a variety of areas in corpus linguistic study, including corpus annotation, data variability, learner language, social media texts, and database utilization. The authors provide critical overviews and research-based analyses, discuss the nature of some of the common pitfalls, and offer solutions to existing problems. 04 09 01 https://benjamins.com/covers/475/scl.118.png 04 03 01 https://benjamins.com/covers/475_jpg/9789027215888.jpg 04 03 01 https://benjamins.com/covers/475_tif/9789027215888.tif 06 09 01 https://benjamins.com/covers/1200_front/scl.118.hb.png 07 09 01 https://benjamins.com/covers/125/scl.118.png 25 09 01 https://benjamins.com/covers/1200_back/scl.118.hb.png 27 09 01 https://benjamins.com/covers/3d_web/scl.118.hb.png 10 01 JB code scl.118.toc v vi 2 Miscellaneous 1 10 01 JB code scl.118.ack vii viii 2 Miscellaneous 2 10 01 JB code scl.118.01kau 1 8 8 Chapter 3 1 A01 Mark Kaunisto Kaunisto, Mark Mark Kaunisto Tampere University 10 01 JB code scl.118.02var 9 34 26 Chapter 4 1 A01 Turo Vartiainen Vartiainen, Turo Turo Vartiainen University of Helsinki 2 A01 Tanja Säily Säily, Tanja Tanja Säily University of Helsinki 20 big data 20 corpus compilation 20 historical corpus linguistics 20 metadata 20 part-of-speech annotation 20 sampling 01 In this chapter, we discuss some common pitfalls related to historical data and its use in linguistic analysis. We argue that the “philologist’s dilemma”, as originally proposed by Rissanen (1989), should be reconceptualized to meet the needs of the fast-evolving field of corpus linguistics, where scholars make increasing use of big-data resources and sophisticated statistical modelling. By providing examples of errors and uncertainties related to, for example, corpus metadata, sampling, balance, and OCR accuracy, we argue that corpus linguists should pay increasingly close attention to the sampling and annotation principles employed in the compilation of historical corpora as well as to the quality of the linguistic data. We propose that the principle of “knowing one’s corpus” in terms of its compilation principles has become all the more important in the age of big-data corpora, where it is not feasible for individual researchers, or corpus compilers, to validate their data manually. 10 01 JB code scl.118.03kau 35 54 20 Chapter 5 1 A01 Mark Kaunisto Kaunisto, Mark Mark Kaunisto Tampere University 20 annotation 20 corpus linguistics 20 named entities 20 proper names 01 This chapter discusses problems in the interpretation of corpus data arising from the insufficiencies in the annotation of named entities. Many corpora nowadays still do not adequately enable corpus users to set up queries that would exclude items appearing in names when needed to improve precision of the searches. Through an examination of case studies in major English language corpora, the chapter highlights the need to carefully post-process the search results, as irrelevant occurrences of named entities may pose challenges in the analyses of word frequencies and their collocational behaviour. The chapter calls for more detailed annotation of named entities in already available large linguistic corpora and reminds of the importance of close inspection of the search hits. 10 01 JB code scl.118.04cal 55 67 13 Chapter 6 1 A01 Marcus Callies Callies, Marcus Marcus Callies University of Bremen 20 analysis 20 annotation 20 compilation 20 discourse of deficit 20 learner corpus 20 lexical bias 20 lexical innovation 20 multilingualism 20 task instruction 20 writing prompt 01 This chapter highlights and discusses the special characteristics of learner corpus data and the challenges they may present for corpus compilation, annotation, and analysis. Because learner corpus and SLA researchers use their data to study L2 production and development, it is of utmost importance that the data are valid, that is, they represent “authentic” L2 production, which means that the data must stem from the studied learners’ own language production. I discuss challenges in three areas: (1) multilingual practices and metalinguistic language use, (2) lexical and constructional bias, often brought about by the wording of task instructions or writing prompts that learners are asked to respond to, and (3) learner corpus annotation in view of the “discourse of deficit” in SLA. For each of these challenges solutions as to how they can be met are offered. 10 01 JB code scl.118.05hil 68 88 21 Chapter 7 1 A01 Turo Hiltunen Hiltunen, Turo Turo Hiltunen University of Helsinki 20 corpus compilation 20 Digital Humanities 20 register 20 representativeness 20 sampling 01 The availability of large digital archives has great potential for corpus linguistic research, but their use is not without problems. These problems can often be traced to fundamentally different ideas of what might constitute “good data” in Digital Humanities and in corpus linguistics, leading to different expectations regarding how the data is made available to researchers. This chapter discusses the specific challenges involved in using the <i>British Library Newspapers</i> database for corpus linguistics and considers potential solutions for them. It is argued that, to take full advantage of the database, it is necessary to adopt a flexible approach enabling a critical reflection on the digital materials, how they have been collected, processed, and made available. 10 01 JB code scl.118.06har 89 105 17 Chapter 8 1 A01 Stefan Hartmann Hartmann, Stefan Stefan Hartmann Heinrich Heine University Düsseldorf 20 accessibility 20 open research 20 replicability 20 representativeness 20 transparency 01 In recent years, many researchers have called attention to the fact that research results very often cannot be replicated – a phenomenon that has been called <i>replication crisis</i>. The replication crisis in linguistics is highly relevant to corpus-based research: Many corpus studies are not directly replicable as the data on which they are based are not readily available. Especially in English linguistics, the full versions of many widely used corpora are still behind paywalls, which means that they are not accessible to parts of the global research community, and even when parts of the data are freely accessible, this presents problems for state-of-the-art methods of data analysis. In this paper, I discuss the challenges that have led to this situation and address some possible solutions. In particular, I argue for using smaller but openly available corpora whenever possible and for adopting open research practices as far as possible even when using commercial corpora. 10 01 JB code scl.118.07lii 106 125 20 Chapter 9 1 A01 Aatu Liimatta Liimatta, Aatu Aatu Liimatta University of Helsinki 20 lengthwise analysis 20 lexical diversity 20 normalization 20 text length 01 Variation in text length is an unavoidable confounder in quantitative text-analytic corpus-linguistic studies. Texts can be difficult to compare across text lengths, particularly if many of them are short, due to the difficulty of calculating meaningful frequencies for the lexical items and linguistic features of interest. Traditionally, this has been less of an issue, since texts in many of the genres typically studied in linguistics have been relatively long. However, the rise of social media has brought the issue to the forefront. In this chapter, I describe the problem of text length and short texts together with a number of solutions and workarounds to this and related problems. 10 01 JB code scl.118.08ihr 126 141 16 Chapter 10 1 A01 Daniel Ocic Ihrmark Ihrmark, Daniel Ocic Daniel Ocic Ihrmark Linnaeus University 20 corpus linguistics 20 genre 20 literature 20 special corpora 20 stylistics 01 This chapter highlights genre categorizations as a pitfall at the intersection of corpus linguistics and literature and problematizes the use of the genre category from the perspectives afforded by both fields. The intention is for the paper to argue for a more explicit communication of our genre categorization practices, and by doing so suggest ways of avoiding miscommunication and confusion due to the genre term being understood differently within different disciplines and backgrounds. The conclusion is that the wider categorizations used, such as <i>novel</i> or <i>short story</i>, are likely to be the most practical, and that studies wanting to sub-categorize further using the genre term should instead apply it according to their specific needs accompanied by explicit discussion of the implementation. 10 01 JB code scl.118.09mil 142 170 29 Chapter 11 1 A01 Filip Miletic Miletic, Filip Filip Miletic CLLE, CNRS & University of Toulouse | IMS, University of Stuttgart 2 A01 Anne Przewozny-Desriaux Przewozny-Desriaux, Anne Anne Przewozny-Desriaux CLLE, CNRS & University of Toulouse 3 A01 Ludovic Tanguy Tanguy, Ludovic Ludovic Tanguy CLLE, CNRS & University of Toulouse 20 language contact 20 large language models 20 Quebec English 20 semantic shifts 20 Twitter corpora 20 word embeddings 01 This chapter examines the use of recent data sources and computational methods to study fine-grained sociolinguistic phenomena. We deploy a custom-built corpus of tweets (Miletić et al. 2020) and neural word embeddings to investigate the use of contact-induced semantic shifts in Quebec English. Drawing on an analysis of 40 lexical items, we show that our approach is beneficial in facilitating manual inspection of vast amounts of data and establishing fine-grained patterns of language variation. While it is affected by a range of noise-related issues, which we describe in detail, coarse-grained annotation provides an efficient way of circumventing them. We use the results filtered in this way to conduct a quantitative analysis of sociolinguistic constraints on contact-induced semantic shifts, further confirming the relevance of our approach. 10 01 JB code scl.118.si 171 172 2 Miscellaneous 12 02 JBENJAMINS John Benjamins Publishing Company 01 John Benjamins Publishing Company Amsterdam/Philadelphia NL 02 September 2024 20240915 2024 John Benjamins B.V. 02 WORLD 01 JB 1 John Benjamins Publishing Company +31 20 6304747 +31 20 6739773 bookorder@benjamins.nl 01 https://benjamins.com 01 WORLD US CA MX 10 20240915 01 02 JB 1 00 115.00 EUR R 02 02 JB 1 00 121.90 EUR R 01 JB 10 bebc +44 1202 712 934 +44 1202 712 913 sales@bebc.co.uk 03 GB 10 20240915 02 02 JB 1 00 97.00 GBP Z 01 JB 2 John Benjamins North America +1 800 562-5666 +1 703 661-1501 benjamins@presswarehouse.com 01 https://benjamins.com 01 US CA MX 10 20240915 01 gen 02 JB 1 00 149.00 USD