Argumentation Mining

The book finishes with a summary of the argumentation mining tasks, a sketch of potential applications, and a--necessarily subjective--outlook for the field.

Author: Manfred Stede

Publisher: Morgan & Claypool Publishers

ISBN: 9781681734606

Category: Computers

Page: 191

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Argumentation mining is an application of natural language processing (NLP) that emerged a few years ago and has recently enjoyed considerable popularity, as demonstrated by a series of international workshops and by a rising number of publications at the major conferences and journals of the field. Its goals are to identify argumentation in text or dialogue; to construct representations of the constellation of claims, supporting and attacking moves (in different levels of detail); and to characterize the patterns of reasoning that appear to license the argumentation. Furthermore, recent work also addresses the difficult tasks of evaluating the persuasiveness and quality of arguments. Some of the linguistic genres that are being studied include legal text, student essays, political discourse and debate, newspaper editorials, scientific writing, and others. The book starts with a discussion of the linguistic perspective, characteristics of argumentative language, and their relationship to certain other notions such as subjectivity. Besides the connection to linguistics, argumentation has for a long time been a topic in Artificial Intelligence, where the focus is on devising adequate representations and reasoning formalisms that capture the properties of argumentative exchange. It is generally very difficult to connect the two realms of reasoning and text analysis, but we are convinced that it should be attempted in the long term, and therefore we also touch upon some fundamentals of reasoning approaches. Then the book turns to its focus, the computational side of mining argumentation in text. We first introduce a number of annotated corpora that have been used in the research. From the NLP perspective, argumentation mining shares subtasks with research fields such as subjectivity and sentiment analysis, semantic relation extraction, and discourse parsing. Therefore, many technical approaches are being borrowed from those (and other) fields. We break argumentation mining into a series of subtasks, starting with the preparatory steps of classifying text as argumentative (or not) and segmenting it into elementary units. Then, central steps are the automatic identification of claims, and finding statements that support or oppose the claim. For certain applications, it is also of interest to compute a full structure of an argumentative constellation of statements. Next, we discuss a few steps that try to 'dig deeper': to infer the underlying reasoning pattern for a textual argument, to reconstruct unstated premises (so-called 'enthymemes'), and to evaluate the quality of the argumentation. We also take a brief look at 'the other side' of mining, i.e., the generation or synthesis of argumentative text. The book finishes with a summary of the argumentation mining tasks, a sketch of potential applications, and a--necessarily subjective--outlook for the field.

Argument Mining

This book is an introduction to the theoretical and linguistic concepts of argumentation and their application to argumentation mining. It partly emerged from a course given at the ESSLLI summer school held in Toulouse in July 2017.

Author: Mathilde Janier

Publisher: John Wiley & Sons

ISBN: 9781786303035

Category: Computers

Page: 202

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This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.

Argumentation Mining Extracting Argumentation Structures in Persuasive Texts

However, argumentation is insufficiently fostered and taught at the moment. In this work, an argumentation feedback tool is built that automatically identifies and classifies argument components in German free-input text.

Author: Sebastian Guggisberg

Publisher:

ISBN: OCLC:1150894901

Category:

Page:

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The ongoing technological progress requires an adaption of the education system so that the current and future workforce possess the necessary skills for transforming job profiles. The required skills that should be focused on in education are creativity, critical thinking, communication, and collaboration. Argumentation can be identified as an additional necessary skill due to its great importance in our daily life for communication and collaboration. However, argumentation is insufficiently fostered and taught at the moment. In this work, an argumentation feedback tool is built that automatically identifies and classifies argument components in German free-input text. The tool was designed in three consecutive design cycles following the Design Science Research methodology. For the first time, the state-of-the- art natural language processing model BERT is applied on the tasks of argument identification and classification and implemented in an argumentation mining tool. The model significantly outperforms the current state-of-the-art model for argumentation mining.

From Opinion Mining to Financial Argument Mining

Kirschner, C., Eckle-Kohler, J., Gurevych, I.: Linking the thoughts: analysis of argumentation structures in scientific publications. In: Proceedings of the Second Workshop on Argumentation Mining, pp. 1–11 (2015) 38.

Author: Chung-Chi Chen

Publisher: Springer Nature

ISBN: 9789811628818

Category:

Page:

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Argument Mining

This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high ...

Author: Mathilde Janier

Publisher: John Wiley & Sons

ISBN: 9781119671046

Category: Computers

Page: 202

View: 953

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This book is an introduction to the linguistic concepts of argumentation relevant for argument mining, an important research and development activity which can be viewed as a highly complex form of information retrieval, requiring high-level natural language processing technology. While the first four chapters develop the linguistic and conceptual aspects of argument expression, the last four are devoted to their application to argument mining. These chapters investigate the facets of argument annotation, as well as argument mining system architectures and evaluation. How annotations may be used to develop linguistic data and how to train learning algorithms is outlined. A simple implementation is then proposed. The book ends with an analysis of non-verbal argumentative discourse. Argument Mining is an introductory book for engineers or students of linguistics, artificial intelligence and natural language processing. Most, if not all, the concepts of argumentation crucial for argument mining are carefully introduced and illustrated in a simple manner.

Computational Models of Argument

7683–7691 (2020) [15] Esuli, A., Sebastiani, F.: Sentiwordnet: A publicly available lexical resource for opinion mining. In: Proceedings of LREC. pp. 417–422 (2006) [16] Habernal, I., Gurevych, I.: Argumentation mining in user-generated ...

Author: H. Prakken

Publisher: IOS Press

ISBN: 9781643681078

Category: Computers

Page: 496

View: 644

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The investigation of computational models of argument is a rich and fascinating interdisciplinary research field with two ultimate aims: the theoretical goal of understanding argumentation as a cognitive phenomenon by modeling it in computer programs, and the practical goal of supporting the development of computer-based systems able to engage in argumentation-related activities with human users or among themselves. The biennial International Conferences on Computational Models of Argument (COMMA) provide a dedicated forum for the presentation and discussion of the latest advancements in the field, and cover both basic research and innovative applications. This book presents the proceedings of COMMA 2020. Due to the Covid-19 pandemic, COMMA 2020 was held as an online event on the originally scheduled dates of 8 -11 September 2020, organised by the University of Perugia, Italy. The book includes 28 full papers and 13 short papers selected from a total of 78 submissions, the abstracts of 3 invited talks and 13 demonstration abstracts. The interdisciplinary nature of the field is reflected, and contributions cover both theory and practice. Theoretical contributions include new formal models, the study of formal or computational properties of models, designs for implemented systems and experimental research. Practical papers include applications to medicine, law and criminal investigation, chatbots and online product reviews. The argument-mining trend from previous COMMA’s is continued, while an emerging trend this year is the use of argumentation for explainable AI. The book provided an overview of the latest work on computational models of argument, and will be of interest to all those working in the field.

Computational Models of Argument

Argumentation mining in user-generated web discourse. Comput. Linguist., 43(1):125–179, 2017. A. Hunter and M. Williams. Aggregating evidence about the positive and negative effects of treatments. Artificial Intelligence in Medicine, ...

Author: S. Modgil

Publisher: IOS Press

ISBN: 9781614999065

Category: Computers

Page: 496

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In its classical form, the study of argumentation focuses on human-oriented uses of argument, such as whether an argument is legitimate or flawed, engagement in debate, or the rhetorical aspects of argumentation. In recent decades, however, the study of logic and computational models of argumentation has emerged as a growing sub-area of AI. This book presents the Seventh International Conference on Computational Models of Argument (COMMA’18), held in Warsaw, Poland, from 12 to 14 September 2018. Since its inception in 2006, the conference and its related activities have developed alongside the steady growth of interest in computational argumentation worldwide, and the selection of 25 full papers and 17 short papers, out of a total of 70 submissions, and 15 demonstration abstracts included here reflect the broad multidisciplinary nature of argumentation and the increasing body of work which establishes the relevance of computational models to various disciplines and real world applications. Subjects covered include: algorithm development; innovative applications; argument mining, argumentation-based models of dialogue; abstract argument frameworks; and structured argumentation. Representing an overview of current developments in the field, this book will appeal to all those with an interest in computational models of argument.

Innovation Through Information Systems

Thus, we built on the application of recent developments in NLP and ML, in which argumentation mining has been a proven approach to identify and analyze argumentative structures of a given text in real time [19, 29, 37, 38].

Author: Frederik Ahlemann

Publisher: Springer Nature

ISBN: 9783030867973

Category:

Page:

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Analysis of Images Social Networks and Texts

Argumentation mining refers to automatic extraction of arguments and their relations from texts. This field has been evolving rapidly in recent years, but there is almost no research for the Russian language.

Author: Wil M. P. van der Aalst

Publisher: Springer Nature

ISBN: 9783030373344

Category: Computers

Page: 426

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This book constitutes the post-conference proceedings of the 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019, held in Kazan, Russia, in July 2019. The 27 full and 8 short papers were carefully reviewed and selected from 134 submissions (of which 21 papers were automatically rejected without being reviewed). The papers are organized in topical sections on general topics of data analysis; natural language processing; social network analysis; analysis of images and video; optimization problems on graphs and network structures; and analysis of dynamic behavior through event data.

From Argument Schemes to Argumentative Relations in the Wild

On bipolarity in argumentation frameworks. International Journal of Intelligent Systems, 23(10), 1062–1093. Bosc, T., Cabrio, E., & Villata, S. (2016). Tweeties squabbling: Positive and negative results in applying argument mining on ...

Author: Frans H. van Eemeren

Publisher: Springer Nature

ISBN: 9783030283674

Category: Philosophy

Page: 289

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This volume comprises a selection of contributions to the theorizing about argumentation that have been presented at the 9th conference of the International Society for the Study of Argumentation (ISSA), held in Amsterdam in July 2018. The chapters included provide a general theoretical perspective on central topics in argumentation theory, such as argument schemes and the fallacies. Some contributions concentrate on the treatment of the concept of conductive argument. Other contributions are dedicated to specific issues such as the justification of questions, the occurrence of mining relations, the role of exclamatives, argumentative abduction, eudaimonistic argumentation and a typology of logical ways to counter an argument. In a number of cases the theoretical problems addressed are related to a specific type of context, such as the burden of proof in philosophical argumentation, the charge of committing a genetic fallacy in strategic manoeuvring in philosophy, the necessity of community argument, and connection adequacy for arguments with institutional warrants. The volume offers a great deal of diversity in its breadth of coverage of argumentation theory and wide geographic representation from North and South America to Europe and China.

Computational Models of Argument

Natural language understanding, Knowledge acquisition, Machine learning Argumentation mining regards an advanced form of human language understanding by the machine. This is a challenging task for a machine.

Author: P. Baroni

Publisher: IOS Press

ISBN: 9781614996866

Category: Computers

Page: 496

View: 175

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Research into computational models of argument is a rich interdisciplinary field involving the study of natural, artificial and theoretical argumentation and requiring openness to interactions with a variety of disciplines, ranging from philosophy and cognitive science to formal logic and graph theory. The ultimate aim is to support the development of computer-based systems able to engage in argumentation-related activities, either with human users or among themselves. This book presents the proceedings of the sixth biennial International Conference on Computational Models of Argument (COMMA 2016), held in Potsdam, Germany, on 12- 16 September. The aim of the COMMA conferences is to bring together researchers interested in computational models of argument and the representation of argumentation structures in natural language texts, with special attention to contributions concerning emerging trends and the development of new connections with other areas. The book contains the 25 full papers, 17 short papers and 10 demonstration abstracts presented at the conference, together with 3 invited talks. Subjects covered include abstract, bipolar and structured argumentation, quantitative approaches and their connections with formalisms like Bayesian networks and fuzzy logic, multi-agent scenarios, algorithms and solvers, and mining arguments in text, dialogue, and social media. The book provides an overview of current research and developments in the field of computational models of argument, and will be essential reading for all those with an interest in the field.

Advances in Databases and Information Systems

Sample on-line argument map generated in Deliberatorium [13] The approaches to argumentation visualization/mapping presented in the previous section ... Argumentation mining is a relatively new challenge in discourse analysis [3,12].

Author: Jaroslav Pokorný

Publisher: Springer

ISBN: 9783319440392

Category: Computers

Page: 354

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This book constitutes the thoroughly refereed proceedings of the 20th East European Conference on Advances in Databases and Information Systems, ADBIS 2016, held in Prague, Czech Republic, in August 2016. The 21 full papers presented together with two keynote papers and one keynote abstract were carefully selected and reviewed from 85 submissions. The papers are organized in topical sections such as data quality, mining, analysis and clustering; model-driven engineering, conceptual modeling; data warehouse and multidimensional modeling, recommender systems; spatial and temporal data processing; distributed and parallel data processing; internet of things and sensor networks.

Legal Knowledge and Information Systems

From argument diagrams to argumentation mining in texts: A survey. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 7(1):1–31, 2013. [16] S. Teufel and M. Moens. Summarizing scientific articles: ...

Author: S. Villata

Publisher: IOS Press

ISBN: 9781643681511

Category: Computers

Page: 302

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The field of legal knowledge and information systems has traditionally been concerned with the subjects of legal knowledge representation and engineering, computational models of legal reasoning, and the analysis of legal data, but recent years have also seen an increasing interest in the application of machine learning methods to ease and empower the everyday activities of legal experts. This book presents the proceedings of the 33rd International Conference on Legal Knowledge and Information Systems (JURIX 2020), organised this year as a virtual event on 9–11 December 2020 due to restrictions resulting from the Covid-19 pandemic. For more than three decades, the annual JURIX international conference, which now also includes demo papers, has provided a platform for academics and practitioners to exchange knowledge about theoretical research and applications in concrete legal use cases. A total of 85 submissions by 255 authors from 28 countries were received for the conference, and after a rigorous review process, 20 were selected for publication as full papers, 14 as short papers, and 5 as demo papers. This selection process resulted in a total acceptance rate of 40% (full and short papers) and a competitive 23.5% acceptance rate for full papers. Topics span from computational models of legal argumentation, case-based reasoning, legal ontologies, smart contracts, privacy management and evidential reasoning to information extraction from different types of text in legal documents, and ethical dilemmas. Providing a state-of-the-art overview of developments in the field, this book will be of interest to all those working with legal knowledge and information systems.

Cognitive Systems and Signal Processing

Springer, Cham (2015). https://doi.org/10.1007/978-3-319-28460-610 Lippi, M., Torroni, P.: Context-independent claim detection for argument mining. IJCAI 15, 185–191 (2015) Lippi, M., Torroni, P.: Argumentation mining: state of the art ...

Author: Fuchun Sun

Publisher: Springer

ISBN: 9789811379833

Category: Computers

Page: 582

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This two-volume set (CCIS 1005 and CCIS 1006) constitutes the refereed proceedings of the 4th International Conference on Cognitive Systems and Signal Processing, ICCSIP2018, held in Beijing, China, in November and December 2018. The 96 revised full papers presented were carefully reviewed and selected from 169 submissions. The papers are organized in topical sections on vision and image; algorithms; robotics; human-computer interaction; deep learning; information processing and automatic driving.

Scientific Reasoning and Argumentation

Proceedings of the First Workshop on Argumentation Mining. Stroudsburg, PA: Association for Computational Linguistics. Greeno, J. G. (1983). Conceptual entities. In D. Gentner & A. Stevens (Eds.), Mental models (pp. 227– 252).

Author: Frank Fischer

Publisher: Routledge

ISBN: 9781351400428

Category: Education

Page: 280

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Competence in scientific reasoning is one of the most valued outcomes of secondary and higher education. However, there is a need for a deeper understanding of and further research into the roles of domain-general and domain-specific knowledge in such reasoning. This book explores the functions and limitations of domain-general conceptions of reasoning and argumentation, the substantial differences that exist between the disciplines, and the role of domain-specific knowledge and epistemologies. Featuring chapters and commentaries by widely cited experts in the learning sciences, educational psychology, science education, history education, and cognitive science, Scientific Reasoning and Argumentation presents new perspectives on a decades-long debate about the role of domain-specific knowledge and its contribution to the development of more general reasoning abilities.

Statistical Language and Speech Processing

Goudas, T., Louizos, C., Petasis, G., Karkaletsis, V.: Argument extraction from news, blogs, and social media. ... Computing Research Repository (CoRR) (2016) Palau, R.M., Moens, M.F.: Argumentation mining: the detection, ...

Author: Nathalie Camelin

Publisher: Springer

ISBN: 9783319684567

Category: Computers

Page: 276

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This book constitutes the refereed proceedings of the 5th International Conference on Statistical Language and Speech Processing, SLSP 2017, held in Le Mans, France, in October 2017. The 21 full papers presented were carefully reviewed and selected from 39 submissions. The papers cover topics such as anaphora and conference resolution; authorship identification, plagiarism and spam filtering; computer-aided translation; corpora and language resources; data mining and semanticweb; information extraction; information retrieval; knowledge representation and ontologies; lexicons and dictionaries; machine translation; multimodal technologies; natural language understanding; neural representation of speech and language; opinion mining and sentiment analysis; parsing; part-of-speech tagging; question and answering systems; semantic role labeling; speaker identification and verification; speech and language generation; speech recognition; speech synthesis; speech transcription; speech correction; spoken dialogue systems; term extraction; text categorization; test summarization; user modeling. They are organized in the following sections: language and information extraction; post-processing and applications of automatic transcriptions; speech paralinguistics and synthesis; speech recognition: modeling and resources.

Digital Transformation and Global Society

Lawrence, J., Reed, C., Allen, C., McAlister, S., Ravenscroft, A.: Mining arguments from 19th century philosophical texts using topic based modelling. In: Proceedings of the First Workshop on Argumentation Mining, pp. 79–87.

Author: Daniel A. Alexandrov

Publisher: Springer Nature

ISBN: 9783030378585

Category: Computers

Page: 779

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This volume constitutes the refereed proceedings of the 4th International Conference on Digital Transformation and Global Society, DTGS 2019, held in St. Petersburg, Russia, in June 2019. The 56 revised full papers and 9 short papers presented in the volume were carefully reviewed and selected from 194 submissions. The papers are organized in topical sections on ​e-polity: governance; e-polity: politics online; e-city: smart cities and urban planning; e-economy: online consumers and solutions; e-society: computational social science; e-society: humanities and education; international workshop on internet psychology; international workshop on computational linguistics.

Experimental IR Meets Multilinguality Multimodality and Interaction

a second one focusing on argument mining in a multilingual collection. It consisted in finding personal and argumentative microblogs in the corpus. Public posts about cultural events like festivals are mostly promotional announcements ...

Author: Patrice Bellot

Publisher: Springer

ISBN: 9783319989327

Category: Computers

Page: 390

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This book constitutes the refereed proceedings of the 9th International Conference of the CLEF Initiative, CLEF 2018, jointly organized by Avignon, Marseille and Toulon universities and held in Avignon, France, in September 2018. The conference has a clear focus on experimental information retrieval with special attention to the challenges of multimodality, multilinguality, and interactive search ranging from unstructured to semi structures and structured data. The 13 papers presented in this volume were carefully reviewed and selected from 39 submissions. Many papers tackle the medical ehealth and ehealth multimedia retrieval challenges, however there are many other topics of research such as document clustering, social biases in IR, social book search, personality profiling. Further this volume presents 9 “best of the labs” papers which were reviewed as a full paper submission with the same review criteria. The labs represented scientific challenges based on new data sets and real world problems in multimodal and multilingual information access. In addition to this, 10 benchmarking labs reported results of their yearlong activities in overview talks and lab sessions. The papers address all aspects of information access in any modularity and language and cover a broad range of topics in the field of multilingual and multimodal information access evaluation.

ADBIS TPDL and EDA 2020 Common Workshops and Doctoral Consortium

Cabrio, E., Villata, S.: Generating abstract arguments: a natural language approach. In: COMMA, pp. 454–461 (2012) 3. Carstens, L., Toni, F., Evripidou, V.: Argument mining and social debates. Argument 2, 3 (2014) 4.

Author: Ladjel Bellatreche

Publisher: Springer Nature

ISBN: 9783030558147

Category:

Page:

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