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Erik Cambria Dipankar Das Sivaji Bandyopadhyay Antonio Feraco Editors a Practical Guide to Sentiment Analysis Socio-Affective Computing

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Erik Cambria Dipankar Das Sivaji Bandyopadhyay Antonio Feraco Editors a Practical Guide to Sentiment Analysis Socio-Affective Computing Socio-Affective Computing 5 Erik Cambria Dipankar Das Sivaji Bandyopadhyay Antonio Feraco Editors A Practical Guide to Sentiment Analysis Socio-Affective Computing Volume 5 Series Editor Amir Hussain, University of Stirling, Stirling, UK Co-Editor Erik Cambria, Nanyang Technological University, Singapore This exciting Book Series aims to publish state-of-the-art research on socially intelligent, affective and multimodal human-machine interaction and systems. It will emphasize the role of affect in social interactions and the humanistic side of affective computing by promoting publications at the cross-roads between engineering and human sciences (including biological, social and cultural aspects of human life). Three broad domains of social and affective computing will be covered by the book series: (1) social computing, (2) affective computing, and (3) interplay of the first two domains (for example, augmenting social interaction through affective computing). Examples of the first domain will include but not limited to: all types of social interactions that contribute to the meaning, interest and richness of our daily life, for example, information produced by a group of people used to provide or enhance the functioning of a system. Examples of the second domain will include, but not limited to: computational and psychological models of emotions, bodily manifestations of affect (facial expressions, posture, behavior, physiology), and affective interfaces and applications (dialogue systems, games, learning etc.). This series will publish works of the highest quality that advance the understanding and practical application of social and affective computing techniques. Research monographs, introductory and advanced level textbooks, volume editions and proceedings will be considered. More information about this series at http://www.springer.com/series/13199 Erik Cambria • Dipankar Das Sivaji Bandyopadhyay • Antonio Feraco Editors A Practical Guide to Sentiment Analysis 123 Editors Erik Cambria Dipankar Das School of Computer Science Computer Science and Engineering and Engineering Department Nanyang Technological University Jadavpur University Singapore, Singapore Kolkata, India Sivaji Bandyopadhyay Antonio Feraco Computer Science Fraunhofer IDM@NTU and Engineering Department Nanyang Technological University Jadavpur University Singapore, Singapore Kolkata, India ISSN 2509-5706 ISSN 2509-5714 (electronic) Socio-Affective Computing ISBN 978-3-319-55392-4 ISBN 978-3-319-55394-8 (eBook) DOI 10.1007/978-3-319-55394-8 Library of Congress Control Number: 2017938021 © Springer International Publishing AG 2017 Chapter 4 is published with kind permission of the Her Majesty the Queen Right of Canada. This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface While sentiment analysis research has become very popular in the past ten years, most companies and researchers still approach it simply as a polarity detection problem. In reality, sentiment analysis is a “suitcase problem” that requires tackling many natural language processing (NLP) subtasks, including microtext analysis, sarcasm detection, anaphora resolution, subjectivity detection, and aspect extrac- tion. In this book, we propose an overview of the main issues and challenges associated with current sentiment analysis research and provide some insights on practical tools and techniques that can be exploited to both advance the state of the art in all sentiment analysis subtasks and explore new areas in the same context. In Chap. 1, we discuss the state of the art of affective computing and sentiment analysis research, including recent deep learning techniques and linguistic patterns for emotion and polarity detection from different modalities, e.g., text and video. In Chap. 2, Bing Liu describes different aspects of sentiment analysis and different types of opinions. In particular, he uses product reviews as examples to introduce general key concepts and definitions that are applicable to all forms of formal and informal opinion text and all kinds of domains including social and political domains. In Chap. 3, Jiwei Li and Eduard Hovy describe possible directions for deeper understanding about what opinions or sentiments are, why people hold them, and why and how their facets are chosen and expressed, helping bridge the gap between psychology/cognitive science and computational approaches. In Chap. 4, Saif Mohammad discusses different sentiment analysis problems and the challenges that are to be faced in order to go beyond simply determining whether a piece of text is positive, negative, or neutral. In particular, the chapter aims to equip researchers and practitioners with pointers to the latest developments in sentiment analysis and encourage more work in the diverse landscape of problems, especially those areas that are relatively less explored. In Chap. 5, Aditya Joshi, Pushpak Bhattacharyya, and Sagar Ahire contrast the process of lexicon creation for a new language or a resource-scarce language from a resource-rich one and, hence, show how the produced sentiment resources can be exploited to solve classic sentiment analysis problems. v vi Preface In Chap. 6, Hongning Wang and ChengXiang Zhai show how generative models can be used to integrate opinionated text data and their companion numerical sentiment ratings, enabling deeper analysis of sentiment and opinions to obtain not only subtopic-level sentiment but also latent relative weights on different subtopics. In Chap. 7, Vasudeva Varma, Litton Kurisinkel, and Priya Radhakrishnan present an overview of general approaches to automated text summarization with more emphasis on extractive summarization techniques. They also describe recent works on extractive summarization and the nature of scoring function for candidate summary. In Chap. 8, Paolo Rosso and Leticia Cagnina describe the very challenging problems of deception detection and opinion spam detection, as lies and spam are becoming increasingly serious issues with the rise, both in size and importance, of social media and public opinion. Finally, in Chap. 9 Federica Bisio et al. describe how to enhance the accuracy of any algorithm for emotion or polarity detection through the integration of commonsense reasoning resources, e.g., by embedding a concept-level knowledge base for sentiment analysis. Singapore, Singapore Erik Cambria Kolkata, India Dipankar Das Kolkata, India Sivaji Bandyopadhyay Singapore, Singapore Antonio Feraco Contents 1 Affective Computing and Sentiment Analysis ............................ 1 Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, and Antonio Feraco 2 Many Facets of Sentiment Analysis ........................................ 11 Bing Liu 3 Reflections on Sentiment/Opinion Analysis ............................... 41 Jiwei Li and Eduard Hovy 4 Challenges in Sentiment Analysis .......................................... 61 Saif M. Mohammad 5 Sentiment Resources: Lexicons and Datasets ............................. 85 Aditya Joshi, Pushpak Bhattacharyya, and Sagar Ahire 6 Generative Models for Sentiment Analysis and Opinion Mining....... 107 Hongning Wang and ChengXiang Zhai 7 Social Media Summarization ............................................... 135 Vasudeva Varma, Litton J. Kurisinkel, and Priya Radhakrishnan 8 Deception Detection and Opinion Spam................................... 155 Paolo Rosso and Leticia C. Cagnina 9 Concept-Level Sentiment Analysis with SenticNet ....................... 173 Federica Bisio, Claudia Meda, Paolo Gastaldo, Rodolfo Zunino, and Erik Cambria Index ............................................................................... 189 vii Chapter 1 Affective Computing and Sentiment Analysis Erik Cambria, Dipankar Das, Sivaji Bandyopadhyay, and Antonio Feraco Abstract Understanding emotions is one of the most important aspects of personal development and growth and, as such, it is a key tile for the emulation of human intelligence. Besides being a important for the advancement of AI, emotion processing is also important for the closely related task of polarity detection. The opportunity automatically to capture the sentiments of the general public
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