326025912 03 01 01 JB John Benjamins Publishing Company 01 JB code SCL 121 Eb 15 9789027246462 06 10.1075/scl.121 13 2024033458 DG 002 02 01 SCL 02 1388-0373 Studies in Corpus Linguistics 121 01 scl.121 01 https://benjamins.com 02 https://benjamins.com/catalog/scl.121 1 B01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d'Azur 2 B01 Harald Lüngen Lüngen, Harald Harald Lüngen Leibniz-Institut für Deutsche Sprache 3 B01 Laura Herzberg Herzberg, Laura Laura Herzberg University of Mannheim 01 eng 275 vi 261 + index 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 06 01 The present volume is intended as a reference book on Wikipedia corpus studies, from corpus construction to exploration and analysis. Wikipedia is a complex object, difficult to manipulate for linguists and corpus researchers. In addition to the encyclopedic articles consulted by millions of users, it contains vast spaces of written discussions, aka talk pages, where Wikipedia authors negotiate the collaborative editing of articles, make evaluations, or discuss related topics. The proposed volume covers Wikipedia articles, their revision histories, and discussions, with a focus on discussions, which have not been studied extensively so far and have also been neglected in previous corpus building efforts. Wikipedia discussions are instances of computer-mediated communication (CMC), thus constituting a completely different, interaction-oriented linguistic genre. Sophisticated tools and methods of linguistic annotation and corpus exploration are needed to exploit the huge and valuable corpus resources that can be constructed from the Wikipedia discussions. The present volume aims at encouraging and facilitating Wikipedia corpus studies, providing standards, recommendations, and innovative methods to build and explore Wikipedia corpora, and presenting corpus studies that make the most of the peculiarities of Wikipedia. 04 09 01 https://benjamins.com/covers/475/scl.121.png 04 03 01 https://benjamins.com/covers/475_jpg/9789027215963.jpg 04 03 01 https://benjamins.com/covers/475_tif/9789027215963.tif 06 09 01 https://benjamins.com/covers/1200_front/scl.121.hb.png 07 09 01 https://benjamins.com/covers/125/scl.121.png 25 09 01 https://benjamins.com/covers/1200_back/scl.121.hb.png 27 09 01 https://benjamins.com/covers/3d_web/scl.121.hb.png 10 01 JB code scl.121.toc v vi 2 Miscellaneous 1 10 01 JB code scl.121.int 1 10 10 Chapter 2 1 A01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d’Azur 2 A01 Harald Lüngen Lüngen, Harald Harald Lüngen Leibniz-Institut für Deutsche Sprache 3 A01 Laura Herzberg Herzberg, Laura Laura Herzberg University of Mannheim 4 A01 Lydia-Mai Ho-Dac Ho-Dac, Lydia-Mai Lydia-Mai Ho-Dac University of Toulouse Jean Jaurès, CLLE 10 01 JB code scl.121.p1 Section header 3 10 01 JB code scl.121.01hod 12 44 33 Chapter 4 1 A01 Lydia-Mai Ho-Dac Ho-Dac, Lydia-Mai Lydia-Mai Ho-Dac University of Toulouse Jean Jaurès, CLLE 20 corpus building 20 TEI CMC-core 20 Wikipedia talk pages 01 This chapter presents the EFG WikiCorpus, a corpus composed of all the <target target-type="index-entry-marker">talk pages</target> dedicated to (co)writing an article in the English, French and German <target target-type="index-entry-marker">Wikipedia</target>s. This chapter explains the place of talk pages in Wikipedia and describes what is the basic structure of a talk page before detailing the building process of the EFG WikiCorpus: from the Wikipedia archives to a TEI resource encoded according to the <target target-type="index-entry-marker">TEI CMC-core</target> schema. It concludes with a quantitative overview of the EFG WikiCorpus and the EFG WikiDemoCorpus, a derived subcorpus used for qualitative analyses in various contributions of this volume. 10 01 JB code scl.121.02kra 45 74 30 Chapter 5 1 A01 Olivier Kraif Kraif, Olivier Olivier Kraif (Université Grenoble Alpes, LIDILEM) 20 parallel corpora 20 sentence alignment 20 translation 20 Wikipedia as a corpus 01 In this article, we address the issue of Wikipedia as a multilingual resource to extract <target target-type="index-entry-marker">parallel corpora</target> that are useful in multilingual terminology extraction or machine translation. While most previous work in this field assumes that Wikipedia is suitable for mining <target target-type="index-entry-marker">comparable corpora</target>, we concentrate on the actual place of translation in the editorial process of Wikipedia to examine the possibility of extracting parallel corpora, that is, texts where source segments can be linked to their translations. After identifying the different projects, tools and recommendations that allow contributors to enrich Wikipedia by exercising their skills as translators, we conduct an experiment in which we download pairs of articles containing translations. We show the importance of performing a temporal alignment of the versions to be downloaded before launching the actual sentence-level <target target-type="index-entry-marker">alignment</target>. This strategy allows us to obtain a large volume of parallel texts with good-quality sentence-to-sentence <target target-type="index-entry-marker">alignment</target>. 10 01 JB code scl.121.p2 75 1 Section header 6 10 01 JB code scl.121.03tan 76 106 31 Chapter 7 1 A01 Ludovic Tanguy Tanguy, Ludovic Ludovic Tanguy University of Toulouse Jean Jaurès, CLLE 2 A01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d’Azur 3 A01 Lydia-Mai Ho-Dac Ho-Dac, Lydia-Mai Lydia-Mai Ho-Dac University of Toulouse Jean Jaurès, CLLE 20 interaction patterns 20 monologues 20 multi-party conversations 20 online discussions 20 Wikipedia talk pages 01 In this chapter we analyze how users interact on <target target-type="index-entry-marker">Wikipedia talk pages</target>, focusing on the patterns that emerge from a large corpus of 5 million threads across three languages. These patterns take three simple features into account: who posts, when they post, and after whom they post. We begin with an overview and a closer examination of some extreme behaviours: threads with the highest number of users and posts, or those with the longest duration. We then propose fine-grained typologies to analyze the content of a sample of monologal and trilogal openings. This analysis allows us to identify recurring behaviours, some of which we consider specific to the Wikipedia and its contributors, and others more common in online discussions. 10 01 JB code scl.121.04her 107 133 27 Chapter 8 1 A01 Laura Herzberg Herzberg, Laura Laura Herzberg University of Mannheim 2 A01 Harald Lüngen Lüngen, Harald Harald Lüngen Leibniz-Institut für Deutsche Sprache 20 CMC 20 computer-mediated communication 20 interactional structures 20 referencing strategies 20 reply relations 20 Wikipedia talk pages 01 This chapter presents the <target target-type="index-entry-marker">annotation</target> and analysis of interpretative <target target-type="index-entry-marker">reply relations</target> on Wikipedia talk pages using data from the WikiDemoCorpus (WDC). Building on an approach of annotating interpretative <target target-type="index-entry-marker">reply relations</target> to analyze these relations in Wikipedia talk page posts, the chapter presents nine reply relation categories found in the German WDC. Additionally, linguistic cues for each category and the Wikipedia discussion pages overall are explained in detail, illustrated through reply relation targets. The results of the linguistic annotation are threefold: First, we provide an annotation scheme that can be used by third parties to produce more data according to their needs. Second, we shed light on and quantify the numerous ways Wikipedia authors reply to each other’s posts on talk pages. Finally, we provide richly annotated data that can be used for further analyses, such as identifying interactional relations on higher levels or training tasks in machine learning algorithms. 10 01 JB code scl.121.05gre 134 154 21 Chapter 9 1 A01 Eva Gredel Gredel, Eva Eva Gredel University of Duisburg-Essen 20 collaboration 20 corpus linguistics 20 discourse 20 metaphors 20 Wikipedia 01 This chapter analyses the discursive construction of <target target-type="index-entry-marker">collaborative</target> text production via <target target-type="index-entry-marker">metaphors</target> on <target target-type="index-entry-marker">talk pages</target> of the English, French, and German Wikipedia. The cross-linguistic study makes use of the <target target-type="index-entry-marker">WikiDemoCorpus</target> (WDC) to qualitatively reveal the source domains of these metaphors. Situated within the framework of <target target-type="index-entry-marker">discourse analysis</target> in the tradition of Foucault (1966, 1969, 1971), the study analyses how Wikipedia authors use metaphors to create a certain point of view in their collaborations on talk pages. Additionally, the <target target-type="index-entry-marker">Wikipedia corpora</target> available at the Leibniz Institute for the German Language (IDS) via the Corpus Search, Management and Analysis System II (COSMAS II) are used for exemplary quantification. Finally, the potential of further corpus linguistics methods for metaphor identification and analysis is discussed. 10 01 JB code scl.121.p3 155 1 Section header 10 10 01 JB code scl.121.06lan 156 177 22 Chapter 11 1 A01 David Laniado Laniado, David David Laniado Eurecat – Technology Centre of Catalonia 2 A01 Michele Mauri Mauri, Michele Michele Mauri Politecnico di Milano 3 A01 Erik Borra Borra, Erik Erik Borra Politecnico di Milano 20 article evolution 20 Contropedia 20 controversy mapping 20 data visualization 20 Wikipedia revision histories 01 Wikipedia is not just a corpus of encyclopedic articles; it also includes an entire edit <target target-type="index-entry-marker">history</target> that details the evolution of each article. However, such records are often unknown to the general public, and too complex for researchers to use. <target target-type="index-entry-marker">Contropedia</target> uses innovative techniques to allow for the visualization, exploration and investigation of the evolution of Wikipedia articles and disputes about their content. This chapter introduces <target target-type="index-entry-marker">Contropedia</target> and provides an in-depth analysis of two articles from the WikiDemoCorpus: the English language article ‘Chiropractic’ and a multilingual comparison of articles on the European migration crisis. These use cases illustrate Contropedia’s visual and analytical modules for analyzing <target target-type="index-entry-marker">controversies</target> within an article and for cross-cultural comparison. 10 01 JB code scl.121.07flo 178 206 29 Chapter 12 1 A01 Fabian Flöck Flöck, Fabian Fabian Flöck 2 A01 Roberto Ulloa Ulloa, Roberto Roberto Ulloa GESIS – Leibniz Institute for the Social Sciences 3 A01 Maribel Acosta Acosta, Maribel Maribel Acosta Technical University of Munich 20 IWAAN 20 visual analytics 20 Wikipedia revision history 20 WikiWho 01 The <target target-type="index-entry-marker">revision histories</target> of Wikipedia articles are a rich source of data about the interactions of editors with each other and with the content, yet they are not straightforward to mine or understand. We describe two tools for visual analytics that support this effort: (i) An interactive browser extension to study word authorship, age, and <target target-type="index-entry-marker">conflict</target> dynamics, which provides an overlay on live Wikipedia articles; and (ii) a novel interactive Jupyter Notebook package that allows us to run analyses of editorial dynamics out-of-the-box and is easily modifiable. Both leverage live data for any article on demand from several Web APIs, centering on our own WikiWho service, providing the most accurate mining of live word-level changes currently available. We show how these tools enable the exploration of the survival of content, productivity of editors, conflict dynamics, and other metrics through low-barrier interfaces while providing the opportunity for more quantitative investigations via access to the notebooks’ underlying data structures. 10 01 JB code scl.121.08pou 207 236 30 Chapter 13 1 A01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d’Azur 2 A01 Marie Chandelier Chandelier, Marie Marie Chandelier Laboratoire BCL Université Côte d’Azur 20 annotation 20 conflicts 20 disagreements 20 pragmatics 20 Wikipedia talk pages 01 Collaborative situations inevitably generate <target target-type="index-entry-marker">disagreements</target> and even <target target-type="index-entry-marker">conflicts</target>. Over the last decade, Wikipedia has been extensively studied, but mostly from the perspective of social sciences. Conflicts have been described in great detail, along with phenomena such as <target target-type="index-entry-marker">quality</target>, coordination, or in relation to maintenance work. However, most of the studies available did not define, nor measure conflicts from a linguistic perspective. The following chapter concentrates on two types of <target target-type="index-entry-marker">speech act</target>s, which we consider to be of particular significance, namely speech acts expressing disagreement on the one hand, and a set of clearly offensive speech acts, such as <target target-type="index-entry-marker">insults</target> or derogatory language, on the other hand. Our approach is <target target-type="index-entry-marker">corpus-based</target>: the two typologies which are presented in our chapter were developed based on an <target target-type="index-entry-marker">annotation of speech acts</target> in a corpus of <target target-type="index-entry-marker">Wikipedia discussions</target> in French, partly extracted from the WikiDemoCorpus. The chapter then expands on the annotation which was carried out, and on the specific features of conflicts and disagreements in Wikipedia. 10 01 JB code scl.121.09car 237 264 28 Chapter 14 1 A01 Guillaume Carbou Carbou, Guillaume Guillaume Carbou Université de Bordeaux, SPH 2 A01 Lydia-Mai Ho-Dac Ho-Dac, Lydia-Mai Lydia-Mai Ho-Dac University of Toulouse Jean Jaurès, CLLE 3 A01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d’Azure 4 A01 Gilles Sahut Sahut, Gilles Gilles Sahut University of Toulouse Jean Jaurès, LERASS 20 conception of “truth” 20 epistemic regime 20 Wikipedia rules 20 Wikipedia talk pages 01 This chapter presents five <target target-type="index-entry-marker">epistemic regimes</target> we defined for characterizing the conception of “truth” that underpin <target target-type="index-entry-marker">debates</target> amongst Wikipedian editors on talk pages. The chapter starts by defining each epistemic regime and how it could be understood according to the Wikipedia rules. Then, we propose a method to evaluate the operationality of these regimes from a corpus standpoint and to analyse to what extent these regimes are adopted by Wikipedians. The analysis of the <target target-type="index-entry-marker">annotation</target> of 324 posts extracted from the French WikiDemoCorpus largely supports our epistemic model and provides new insights into the ideological backgrounds of Wikipedians. 10 01 JB code scl.121.index 265 266 2 Miscellaneous 15 02 JBENJAMINS John Benjamins Publishing Company 01 John Benjamins Publishing Company Amsterdam/Philadelphia NL 02 October 2024 20241015 2024 John Benjamins B.V. 02 WORLD 13 15 9789027215963 01 JB 3 John Benjamins e-Platform 03 jbe-platform.com 09 WORLD 10 20241015 01 00 120.00 EUR R 01 00 101.00 GBP Z 01 gen 00 156.00 USD S 525025911 03 01 01 JB John Benjamins Publishing Company 01 JB code SCL 121 Hb 15 9789027215963 13 2024033457 BB 01 SCL 02 1388-0373 Studies in Corpus Linguistics 121 01 scl.121 01 https://benjamins.com 02 https://benjamins.com/catalog/scl.121 1 B01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d'Azur 2 B01 Harald Lüngen Lüngen, Harald Harald Lüngen Leibniz-Institut für Deutsche Sprache 3 B01 Laura Herzberg Herzberg, Laura Laura Herzberg University of Mannheim 01 eng 275 vi 261 + index 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 06 01 The present volume is intended as a reference book on Wikipedia corpus studies, from corpus construction to exploration and analysis. Wikipedia is a complex object, difficult to manipulate for linguists and corpus researchers. In addition to the encyclopedic articles consulted by millions of users, it contains vast spaces of written discussions, aka talk pages, where Wikipedia authors negotiate the collaborative editing of articles, make evaluations, or discuss related topics. The proposed volume covers Wikipedia articles, their revision histories, and discussions, with a focus on discussions, which have not been studied extensively so far and have also been neglected in previous corpus building efforts. Wikipedia discussions are instances of computer-mediated communication (CMC), thus constituting a completely different, interaction-oriented linguistic genre. Sophisticated tools and methods of linguistic annotation and corpus exploration are needed to exploit the huge and valuable corpus resources that can be constructed from the Wikipedia discussions. The present volume aims at encouraging and facilitating Wikipedia corpus studies, providing standards, recommendations, and innovative methods to build and explore Wikipedia corpora, and presenting corpus studies that make the most of the peculiarities of Wikipedia. 04 09 01 https://benjamins.com/covers/475/scl.121.png 04 03 01 https://benjamins.com/covers/475_jpg/9789027215963.jpg 04 03 01 https://benjamins.com/covers/475_tif/9789027215963.tif 06 09 01 https://benjamins.com/covers/1200_front/scl.121.hb.png 07 09 01 https://benjamins.com/covers/125/scl.121.png 25 09 01 https://benjamins.com/covers/1200_back/scl.121.hb.png 27 09 01 https://benjamins.com/covers/3d_web/scl.121.hb.png 10 01 JB code scl.121.toc v vi 2 Miscellaneous 1 10 01 JB code scl.121.int 1 10 10 Chapter 2 1 A01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d’Azur 2 A01 Harald Lüngen Lüngen, Harald Harald Lüngen Leibniz-Institut für Deutsche Sprache 3 A01 Laura Herzberg Herzberg, Laura Laura Herzberg University of Mannheim 4 A01 Lydia-Mai Ho-Dac Ho-Dac, Lydia-Mai Lydia-Mai Ho-Dac University of Toulouse Jean Jaurès, CLLE 10 01 JB code scl.121.p1 Section header 3 10 01 JB code scl.121.01hod 12 44 33 Chapter 4 1 A01 Lydia-Mai Ho-Dac Ho-Dac, Lydia-Mai Lydia-Mai Ho-Dac University of Toulouse Jean Jaurès, CLLE 20 corpus building 20 TEI CMC-core 20 Wikipedia talk pages 01 This chapter presents the EFG WikiCorpus, a corpus composed of all the <target target-type="index-entry-marker">talk pages</target> dedicated to (co)writing an article in the English, French and German <target target-type="index-entry-marker">Wikipedia</target>s. This chapter explains the place of talk pages in Wikipedia and describes what is the basic structure of a talk page before detailing the building process of the EFG WikiCorpus: from the Wikipedia archives to a TEI resource encoded according to the <target target-type="index-entry-marker">TEI CMC-core</target> schema. It concludes with a quantitative overview of the EFG WikiCorpus and the EFG WikiDemoCorpus, a derived subcorpus used for qualitative analyses in various contributions of this volume. 10 01 JB code scl.121.02kra 45 74 30 Chapter 5 1 A01 Olivier Kraif Kraif, Olivier Olivier Kraif (Université Grenoble Alpes, LIDILEM) 20 parallel corpora 20 sentence alignment 20 translation 20 Wikipedia as a corpus 01 In this article, we address the issue of Wikipedia as a multilingual resource to extract <target target-type="index-entry-marker">parallel corpora</target> that are useful in multilingual terminology extraction or machine translation. While most previous work in this field assumes that Wikipedia is suitable for mining <target target-type="index-entry-marker">comparable corpora</target>, we concentrate on the actual place of translation in the editorial process of Wikipedia to examine the possibility of extracting parallel corpora, that is, texts where source segments can be linked to their translations. After identifying the different projects, tools and recommendations that allow contributors to enrich Wikipedia by exercising their skills as translators, we conduct an experiment in which we download pairs of articles containing translations. We show the importance of performing a temporal alignment of the versions to be downloaded before launching the actual sentence-level <target target-type="index-entry-marker">alignment</target>. This strategy allows us to obtain a large volume of parallel texts with good-quality sentence-to-sentence <target target-type="index-entry-marker">alignment</target>. 10 01 JB code scl.121.p2 75 1 Section header 6 10 01 JB code scl.121.03tan 76 106 31 Chapter 7 1 A01 Ludovic Tanguy Tanguy, Ludovic Ludovic Tanguy University of Toulouse Jean Jaurès, CLLE 2 A01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d’Azur 3 A01 Lydia-Mai Ho-Dac Ho-Dac, Lydia-Mai Lydia-Mai Ho-Dac University of Toulouse Jean Jaurès, CLLE 20 interaction patterns 20 monologues 20 multi-party conversations 20 online discussions 20 Wikipedia talk pages 01 In this chapter we analyze how users interact on <target target-type="index-entry-marker">Wikipedia talk pages</target>, focusing on the patterns that emerge from a large corpus of 5 million threads across three languages. These patterns take three simple features into account: who posts, when they post, and after whom they post. We begin with an overview and a closer examination of some extreme behaviours: threads with the highest number of users and posts, or those with the longest duration. We then propose fine-grained typologies to analyze the content of a sample of monologal and trilogal openings. This analysis allows us to identify recurring behaviours, some of which we consider specific to the Wikipedia and its contributors, and others more common in online discussions. 10 01 JB code scl.121.04her 107 133 27 Chapter 8 1 A01 Laura Herzberg Herzberg, Laura Laura Herzberg University of Mannheim 2 A01 Harald Lüngen Lüngen, Harald Harald Lüngen Leibniz-Institut für Deutsche Sprache 20 CMC 20 computer-mediated communication 20 interactional structures 20 referencing strategies 20 reply relations 20 Wikipedia talk pages 01 This chapter presents the <target target-type="index-entry-marker">annotation</target> and analysis of interpretative <target target-type="index-entry-marker">reply relations</target> on Wikipedia talk pages using data from the WikiDemoCorpus (WDC). Building on an approach of annotating interpretative <target target-type="index-entry-marker">reply relations</target> to analyze these relations in Wikipedia talk page posts, the chapter presents nine reply relation categories found in the German WDC. Additionally, linguistic cues for each category and the Wikipedia discussion pages overall are explained in detail, illustrated through reply relation targets. The results of the linguistic annotation are threefold: First, we provide an annotation scheme that can be used by third parties to produce more data according to their needs. Second, we shed light on and quantify the numerous ways Wikipedia authors reply to each other’s posts on talk pages. Finally, we provide richly annotated data that can be used for further analyses, such as identifying interactional relations on higher levels or training tasks in machine learning algorithms. 10 01 JB code scl.121.05gre 134 154 21 Chapter 9 1 A01 Eva Gredel Gredel, Eva Eva Gredel University of Duisburg-Essen 20 collaboration 20 corpus linguistics 20 discourse 20 metaphors 20 Wikipedia 01 This chapter analyses the discursive construction of <target target-type="index-entry-marker">collaborative</target> text production via <target target-type="index-entry-marker">metaphors</target> on <target target-type="index-entry-marker">talk pages</target> of the English, French, and German Wikipedia. The cross-linguistic study makes use of the <target target-type="index-entry-marker">WikiDemoCorpus</target> (WDC) to qualitatively reveal the source domains of these metaphors. Situated within the framework of <target target-type="index-entry-marker">discourse analysis</target> in the tradition of Foucault (1966, 1969, 1971), the study analyses how Wikipedia authors use metaphors to create a certain point of view in their collaborations on talk pages. Additionally, the <target target-type="index-entry-marker">Wikipedia corpora</target> available at the Leibniz Institute for the German Language (IDS) via the Corpus Search, Management and Analysis System II (COSMAS II) are used for exemplary quantification. Finally, the potential of further corpus linguistics methods for metaphor identification and analysis is discussed. 10 01 JB code scl.121.p3 155 1 Section header 10 10 01 JB code scl.121.06lan 156 177 22 Chapter 11 1 A01 David Laniado Laniado, David David Laniado Eurecat – Technology Centre of Catalonia 2 A01 Michele Mauri Mauri, Michele Michele Mauri Politecnico di Milano 3 A01 Erik Borra Borra, Erik Erik Borra Politecnico di Milano 20 article evolution 20 Contropedia 20 controversy mapping 20 data visualization 20 Wikipedia revision histories 01 Wikipedia is not just a corpus of encyclopedic articles; it also includes an entire edit <target target-type="index-entry-marker">history</target> that details the evolution of each article. However, such records are often unknown to the general public, and too complex for researchers to use. <target target-type="index-entry-marker">Contropedia</target> uses innovative techniques to allow for the visualization, exploration and investigation of the evolution of Wikipedia articles and disputes about their content. This chapter introduces <target target-type="index-entry-marker">Contropedia</target> and provides an in-depth analysis of two articles from the WikiDemoCorpus: the English language article ‘Chiropractic’ and a multilingual comparison of articles on the European migration crisis. These use cases illustrate Contropedia’s visual and analytical modules for analyzing <target target-type="index-entry-marker">controversies</target> within an article and for cross-cultural comparison. 10 01 JB code scl.121.07flo 178 206 29 Chapter 12 1 A01 Fabian Flöck Flöck, Fabian Fabian Flöck 2 A01 Roberto Ulloa Ulloa, Roberto Roberto Ulloa GESIS – Leibniz Institute for the Social Sciences 3 A01 Maribel Acosta Acosta, Maribel Maribel Acosta Technical University of Munich 20 IWAAN 20 visual analytics 20 Wikipedia revision history 20 WikiWho 01 The <target target-type="index-entry-marker">revision histories</target> of Wikipedia articles are a rich source of data about the interactions of editors with each other and with the content, yet they are not straightforward to mine or understand. We describe two tools for visual analytics that support this effort: (i) An interactive browser extension to study word authorship, age, and <target target-type="index-entry-marker">conflict</target> dynamics, which provides an overlay on live Wikipedia articles; and (ii) a novel interactive Jupyter Notebook package that allows us to run analyses of editorial dynamics out-of-the-box and is easily modifiable. Both leverage live data for any article on demand from several Web APIs, centering on our own WikiWho service, providing the most accurate mining of live word-level changes currently available. We show how these tools enable the exploration of the survival of content, productivity of editors, conflict dynamics, and other metrics through low-barrier interfaces while providing the opportunity for more quantitative investigations via access to the notebooks’ underlying data structures. 10 01 JB code scl.121.08pou 207 236 30 Chapter 13 1 A01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d’Azur 2 A01 Marie Chandelier Chandelier, Marie Marie Chandelier Laboratoire BCL Université Côte d’Azur 20 annotation 20 conflicts 20 disagreements 20 pragmatics 20 Wikipedia talk pages 01 Collaborative situations inevitably generate <target target-type="index-entry-marker">disagreements</target> and even <target target-type="index-entry-marker">conflicts</target>. Over the last decade, Wikipedia has been extensively studied, but mostly from the perspective of social sciences. Conflicts have been described in great detail, along with phenomena such as <target target-type="index-entry-marker">quality</target>, coordination, or in relation to maintenance work. However, most of the studies available did not define, nor measure conflicts from a linguistic perspective. The following chapter concentrates on two types of <target target-type="index-entry-marker">speech act</target>s, which we consider to be of particular significance, namely speech acts expressing disagreement on the one hand, and a set of clearly offensive speech acts, such as <target target-type="index-entry-marker">insults</target> or derogatory language, on the other hand. Our approach is <target target-type="index-entry-marker">corpus-based</target>: the two typologies which are presented in our chapter were developed based on an <target target-type="index-entry-marker">annotation of speech acts</target> in a corpus of <target target-type="index-entry-marker">Wikipedia discussions</target> in French, partly extracted from the WikiDemoCorpus. The chapter then expands on the annotation which was carried out, and on the specific features of conflicts and disagreements in Wikipedia. 10 01 JB code scl.121.09car 237 264 28 Chapter 14 1 A01 Guillaume Carbou Carbou, Guillaume Guillaume Carbou Université de Bordeaux, SPH 2 A01 Lydia-Mai Ho-Dac Ho-Dac, Lydia-Mai Lydia-Mai Ho-Dac University of Toulouse Jean Jaurès, CLLE 3 A01 Céline Poudat Poudat, Céline Céline Poudat Laboratoire BCL Université Côte d’Azure 4 A01 Gilles Sahut Sahut, Gilles Gilles Sahut University of Toulouse Jean Jaurès, LERASS 20 conception of “truth” 20 epistemic regime 20 Wikipedia rules 20 Wikipedia talk pages 01 This chapter presents five <target target-type="index-entry-marker">epistemic regimes</target> we defined for characterizing the conception of “truth” that underpin <target target-type="index-entry-marker">debates</target> amongst Wikipedian editors on talk pages. The chapter starts by defining each epistemic regime and how it could be understood according to the Wikipedia rules. Then, we propose a method to evaluate the operationality of these regimes from a corpus standpoint and to analyse to what extent these regimes are adopted by Wikipedians. The analysis of the <target target-type="index-entry-marker">annotation</target> of 324 posts extracted from the French WikiDemoCorpus largely supports our epistemic model and provides new insights into the ideological backgrounds of Wikipedians. 10 01 JB code scl.121.index 265 266 2 Miscellaneous 15 02 JBENJAMINS John Benjamins Publishing Company 01 John Benjamins Publishing Company Amsterdam/Philadelphia NL 02 October 2024 20241015 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 20241015 01 02 JB 1 00 120.00 EUR R 02 02 JB 1 00 127.20 EUR R 01 JB 10 bebc +44 1202 712 934 +44 1202 712 913 sales@bebc.co.uk 03 GB 10 20241015 02 02 JB 1 00 101.00 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 20241015 01 gen 02 JB 1 00 156.00 USD