Mapping the Public Voice for Development—Natural Language Processing of Social Media Text Data

Mapping the Public Voice for Development—Natural Language Processing of Social Media Text Data PDF Author: Asian Development Bank
Publisher: Asian Development Bank
ISBN: 9292697021
Category : Technology & Engineering
Languages : en
Pages : 159

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Book Description
The publication introduces the foundations of natural language analyses and showcases studies that have applied NLP techniques to make progress on the Sustainable Development Goals. It also reviews specific NLP techniques and concepts, supported by two case studies. The first case study analyzes public sentiments on the coronavirus disease (COVID-19) in the Philippines while the second case study explores the public debate on climate change in Australia.

Mapping the Public Voice for Development—Natural Language Processing of Social Media Text Data

Mapping the Public Voice for Development—Natural Language Processing of Social Media Text Data PDF Author: Asian Development Bank
Publisher: Asian Development Bank
ISBN: 9292697021
Category : Technology & Engineering
Languages : en
Pages : 159

Get Book Here

Book Description
The publication introduces the foundations of natural language analyses and showcases studies that have applied NLP techniques to make progress on the Sustainable Development Goals. It also reviews specific NLP techniques and concepts, supported by two case studies. The first case study analyzes public sentiments on the coronavirus disease (COVID-19) in the Philippines while the second case study explores the public debate on climate change in Australia.

Mapping the Public Voice for Development-Natural Language Processing of Social Media Text Data

Mapping the Public Voice for Development-Natural Language Processing of Social Media Text Data PDF Author: Asian Development Bank
Publisher:
ISBN: 9789292697013
Category :
Languages : en
Pages : 0

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Book Description
This publication explores how natural language processing (NLP) techniques can be applied to social media text data to map public sentiment and inform development research and policy making. The publication introduces the foundations of natural language analyses and showcases studies that have applied NLP techniques to make progress on the Sustainable Development Goals. It also reviews specific NLP techniques and concepts, supported by two case studies. The first case study analyzes public sentiments on the coronavirus disease (COVID-19) in the Philippines while the second case study explores the public debate on climate change in Australia.

Natural Language Processing for Social Media

Natural Language Processing for Social Media PDF Author: Atefeh Farzindar
Publisher: Morgan & Claypool Publishers
ISBN: 1681733277
Category : Computers
Languages : en
Pages : 242

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Book Description
In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.

Building Smarter Data Systems Leveraging Generative AI and Deep Learning

Building Smarter Data Systems Leveraging Generative AI and Deep Learning PDF Author: Arun Kumar Ramachandran Sumangala Devi
Publisher: JEC PUBLICATION
ISBN: 9361753290
Category : Computers
Languages : en
Pages : 171

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Book Description
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Natural Language Processing with SAS

Natural Language Processing with SAS PDF Author:
Publisher:
ISBN: 9781952363184
Category :
Languages : en
Pages : 74

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Book Description
Natural Language Processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret, and emulate written or spoken human language. NLP draws from many disciplines including human-generated linguistic rules, machine learning, and deep learning to fill the gap between human communication and machine understanding. The papers included in this special collection demonstrate how NLP can be used to scale the human act of reading, organizing, and quantifying text data.

Speech & Language Processing

Speech & Language Processing PDF Author: Dan Jurafsky
Publisher: Pearson Education India
ISBN: 9788131716724
Category :
Languages : en
Pages : 912

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Book Description


Natural Language Processing in Artificial Intelligence

Natural Language Processing in Artificial Intelligence PDF Author: Brojo Kishore Mishra
Publisher: CRC Press
ISBN: 1000711315
Category : Science
Languages : en
Pages : 297

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Book Description
This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.

Influence and Escalation

Influence and Escalation PDF Author: Rebecca Hersman
Publisher: Rowman & Littlefield
ISBN: 1538140462
Category : Political Science
Languages : en
Pages : 71

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Book Description
Technology-enabled influence operations, including disinformation, will likely figure prominently in adversary efforts to impede U.S. crisis response and alliance management in high-risk, high-impact scenarios under a nuclear shadow. Both Russia and China recognize their conventional military disadvantage vis-à-vis conflict with the United States. As a result, both nations use sub-conventional tactics and operations to support their preferred strategies for achieving favorable outcomes while attempting to limit escalation risks. Such strategies include an array of activities loosely identified as influence operations, focused on using and manipulating information in covert, deniable, or obscure ways to shape the strategic environment. This report presents eight scenarios—four focused on Russia and four focused on China—that invite potential escalation risks and demonstrate how the tools and tactics of influence operations could be employed to challenge detection, response, and crisis management. It explores a range of potential escalatory pathways and destabilizing consequences if adversary influence operations engage strategic interests and targets in high-risk scenarios and identifies key takeaways and recommendations for policymakers to better identify and defend against adversary influence operations.

Applied Natural Language Processing in the Enterprise

Applied Natural Language Processing in the Enterprise PDF Author: Ankur A. Patel
Publisher: "O'Reilly Media, Inc."
ISBN: 1492062545
Category : Computers
Languages : en
Pages : 336

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Book Description
NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production

Qualitative Text Analysis

Qualitative Text Analysis PDF Author: Udo Kuckartz
Publisher: SAGE
ISBN: 1446297764
Category : Reference
Languages : en
Pages : 193

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Book Description
How can you analyse narratives, interviews, field notes, or focus group data? Qualitative text analysis is ideal for these types of data and this textbook provides a hands-on introduction to the method and its theoretical underpinnings. It offers step-by-step instructions for implementing the three principal types of qualitative text analysis: thematic, evaluative, and type-building. Special attention is paid to how to present your results and use qualitative data analysis software packages, which are highly recommended for use in combination with qualitative text analysis since they allow for fast, reliable, and more accurate analysis. The book shows in detail how to use software, from transcribing the verbal data to presenting and visualizing the results. The book is intended for Master’s and Doctoral students across the social sciences and for all researchers concerned with the systematic analysis of texts of any kind.