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This book adopts a multi-method multimodal approach to the study of online political communication, applying it to case studies from the UK, France, and Italy toward offering a portrait of the rapid ideological shifts in contemporary Western democracies. The volume introduces an integrated framework combining Sentiment and Emotion Analysis, rooted in lexical semantics, and the qualitative dimensions of Appraisal Theory, applying it to large corpora of online political communication from the UK, France, and Italy. Combei and Reggi highlight their combined potential in analyzing the multimodal resources in such discourses and in turn, revealing fresh insights into layers of subtext and the ways in which parties and movements frame their political programmes and values. The authors also take into account culture- and language-specific variables across the three countries in shaping such discourses. The volume makes the case for an integrated methodological framework that can be uniquely applied to better understand the multimodal communicative landscape of divisiveness in today’s rapidly shifting political climate and other forms of online communication more broadly. This book will be of interest to students and scholars in digital communication, political communication, multimodality, and qualitative and quantitative discourse analysis, especially those interested in corpus-assisted approaches.
Sentiment analysis is the computational study of people's opinions, sentiments, emotions, moods, and attitudes. This fascinating problem offers numerous research challenges, but promises insight useful to anyone interested in opinion analysis and social media analysis. This comprehensive introduction to the topic takes a natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs commonly used to express opinions, sentiments, and emotions. The book covers core areas of sentiment analysis and also includes related topics such as debate analysis, intention mining, and fake-opinion detection. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. In addition to traditional computational methods, this second edition includes recent deep learning methods to analyze and summarize sentiments and opinions, and also new material on emotion and mood analysis techniques, emotion-enhanced dialogues, and multimodal emotion analysis.
This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography
The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
This collection responds to the need for theoretically informed and methodologically grounded empirical research on the global transformations in multimodal human communication and social practices in light of recent widespread change. The volume highlights the need to expand on the established approaches--Social Semiotics, Multimodal Discourse Analysis, and Multimodal (Inter)action Analysis--by complementing them with other analytical frameworks to better understand the impact of unprecedented global challenges, such as Covid-19, on the way humans communicate and make use of meaning-making resources. Bringing together established and emergent scholars from a variety of geographical, cultural, and linguistic contexts, the collection presents studies from both the Global North and Global South, including South Africa, Latin America, Brazil, and the Caribbean, to showcase new perspectives in multimodality research. This innovative book will be of interest to students and scholars in multimodality, social semiotics, and discourse analysis.
Paradoxically, the term 'rhetoric' functions nowadays both as a name of an antique, even obsolete framework of research and as a fashionable buzzword that entails virtually any form of persuasive communication. Reflecting a growing scholarly interest in political discourses, this volume offers systematic, theoretically grounded insights into the flow of persuasion that constitutes politics today. Authors combine the interest in rhetoric within politics with different disciplinary orientations ...
Emotions work to define who we are as well as shape what we do and this is no more powerfully at play than in the world of politics. Ahmed considers how emotions keep us invested in relationships of power, and also shows how this use of emotion could be crucial to areas such as feminist and queer politics. Debates on international terrorism, asylum and migration, as well as reconciliation and reparation, are explored through topical case studies. In this book the difficult issues are confronted head on. The Cultural Politics of Emotion is in dialogue with recent literature on emotions within gender studies, cultural studies, sociology, psychology and philosophy. Throughout the book, Ahmed develops a theory of how emotions work, and the effects they have on our day-to-day lives. New for this editionA substantial 15,000-word Afterword on 'Emotions and Their Objects' which provides an original contribution to the burgeoning field of affect studiesA revised BibliographyUpdated throughout.
This volume maps the watershed areas between two 'holy grails' of computer science: the identification and interpretation of affect – including sentiment and mood. The expression of sentiment and mood involves the use of metaphors, especially in emotive situations. Affect computing is rooted in hermeneutics, philosophy, political science and sociology, and is now a key area of research in computer science. The 24/7 news sites and blogs facilitate the expression and shaping of opinion locally and globally. Sentiment analysis, based on text and data mining, is being used in the looking at news and blogs for purposes as diverse as: brand management, film reviews, financial market analysis and prediction, homeland security. There are systems that learn how sentiments are articulated. This work draws on, and informs, research in fields as varied as artificial intelligence, especially reasoning and machine learning, corpus-based information extraction, linguistics, and psychology.