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50.1 Introduction 50.1 Introduction
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50.2 Availability of Tools and Resources in Computational Linguistics 50.2 Availability of Tools and Resources in Computational Linguistics
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50.2.1 Frameworks, APIs, and Toolkits for Language Processing 50.2.1 Frameworks, APIs, and Toolkits for Language Processing
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50.2.2 Cloud Computing and Language Processing APIs 50.2.2 Cloud Computing and Language Processing APIs
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50.2.3 Processing Large Collections of Documents 50.2.3 Processing Large Collections of Documents
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50.2.4 Access to Linguistic Resources 50.2.4 Access to Linguistic Resources
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50.3 Processing of User-Generated Content 50.3 Processing of User-Generated Content
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50.3.1 Dealing with Particularities of the UGC 50.3.1 Dealing with Particularities of the UGC
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50.3.2 Recent Work in Sentiment Analysis and Opinion Mining 50.3.2 Recent Work in Sentiment Analysis and Opinion Mining
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50.3.2.1 Sarcasm and irony detection 50.3.2.1 Sarcasm and irony detection
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50.3.2.2 Negation and speculation detection 50.3.2.2 Negation and speculation detection
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50.3.3 Automatic Assessment of User-Generated Content 50.3.3 Automatic Assessment of User-Generated Content
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50.3.4 Automatic Stance Detection 50.3.4 Automatic Stance Detection
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50.3.5 Aggression Identification 50.3.5 Aggression Identification
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50.4 Crowdsourcing for the Creation of Linguistic Resources 50.4 Crowdsourcing for the Creation of Linguistic Resources
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50.5 Processing of Texts for Financial Purposes 50.5 Processing of Texts for Financial Purposes
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50.6 NLP for Users with Disabilities and for the Mental Health Sector 50.6 NLP for Users with Disabilities and for the Mental Health Sector
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50.7 Natural Language Processing for Educational Applications 50.7 Natural Language Processing for Educational Applications
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50.8 Language and Vision 50.8 Language and Vision
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50.9 Chatbots and Conversational Agents 50.9 Chatbots and Conversational Agents
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Further Reading and Relevant Resources Further Reading and Relevant Resources
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Acknowledgements Acknowledgements
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References References
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50 Recent Developments in Natural Language Processing
Get accessConstantin Orăsan is Professor of Language and Translation Technologies at the Centre of Translation Studies, University of Surrey, UK. Previously, he was Reader in Computational Linguistics at the University of Wolverhampton, UK. His research interests are largely focused on facilitating information access, and include translation technology, text simplification/accessibility, text summarization, and NLP for social media. He has published over 100 peer-reviewed articles in journals, books, and proceedings of international conferences. His personal website is https://dinel.org.uk.
Ruslan Mitkov’s research covers 250 publications on various topics of Natural Language Processing. He is author of the monograph Anaphora Resolution (Longman, 2002), Editor of The Oxford Handbook of Computational Linguistics (Oxford University Press), Executive Editor of the Journal of Natural Language Engineering (Cambridge University Press), Editor-in-Chief of the John Benjamins NLP book series, and has been programme chair and keynote speaker of many international conferences. He is Director of the Research Institute in Information and Language Processing at the University of Wolverhampton. In recognition of his outstanding research/professional achievements, he has twice been awarded the title of Doctor honoris causa.
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Published:10 February 2021
Cite
Abstract
Natural Language Processing (NLP) is a dynamic and rapidly developing field in which new trends, techniques, and applications are constantly emerging. This chapter focuses mainly on recent developments in NLP which could not be covered in other chapters of the Handbook. Topics such as crowdsourcing and processing of large datasets, which are no longer that recent but are widely used and not covered at length in any other chapter, are also presented. The chapter starts by describing how the availability of tools and resources has had a positive impact on the field. The proliferation of user-generated content has led to the emergence of research topics such as sarcasm and irony detection, automatic assessment of user-generated content, and stance detection. All of these topics are discussed in the chapter. The field of NLP is approaching maturity, a fact corroborated by the latest developments in the processing of texts for financial purposes and for helping users with disabilities, two topics that are also discussed here. The chapter presents examples of how researchers have successfully combined research in computer vision and natural language processing to enable the processing of multimodal information, as well as how the latest advances in deep learning have revitalized research on chatbots and conversational agents. The chapter concludes with a comprehensive list of further reading material and additional resources.
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