Opinion Mining And Sentiment Analysis

Author : Bing Liu
Publisher : Springer Nature
Page : 167 pages
File Size : 48,7 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031021459

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Sentiment Analysis and Opinion Mining by Bing Liu Pdf

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

Author : Bo Pang,Lillian Lee
Publisher : Now Publishers Inc
Page : 149 pages
File Size : 48,5 Mb
Release : 2008
Category : Data mining
ISBN : 9781601981509

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Opinion Mining and Sentiment Analysis by Bo Pang,Lillian Lee Pdf

This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.

Author : Bing Liu
Publisher : Cambridge University Press
Page : 451 pages
File Size : 50,5 Mb
Release : 2020-10-15
Category : Business & Economics
ISBN : 9781108486378

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Sentiment Analysis by Bing Liu Pdf

A comprehensive introduction to computational analysis of sentiments, opinions, emotions, and moods. Now including deep learning methods.

Author : Bing Liu
Publisher : Morgan & Claypool Publishers
Page : 185 pages
File Size : 40,9 Mb
Release : 2012
Category : Computers
ISBN : 9781608458844

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Sentiment Analysis and Opinion Mining by Bing Liu Pdf

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

Author : Julia Silge,David Robinson
Publisher : "O'Reilly Media, Inc."
Page : 193 pages
File Size : 50,5 Mb
Release : 2017-06-12
Category : Computers
ISBN : 9781491981627

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Text Mining with R by Julia Silge,David Robinson Pdf

Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.

Author : Juan D. Velásquez,Vasile Palade,Lakhmi C. Jain
Publisher : Springer
Page : 184 pages
File Size : 44,5 Mb
Release : 2012-09-29
Category : Technology & Engineering
ISBN : 9783642333262

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Advanced Techniques in Web Intelligence-2 by Juan D. Velásquez,Vasile Palade,Lakhmi C. Jain Pdf

This research volume focuses on analyzing the web user browsing behaviour and preferences in traditional web-based environments, social networks and web 2.0 applications, by using advanced techniques in data acquisition, data processing, pattern extraction and cognitive science for modeling the human actions. The book is directed to graduate students, researchers/scientists and engineers interested in updating their knowledge with the recent trends in web user analysis, for developing the next generation of web-based systems and applications.

Author : Federico Alberto Pozzi,Elisabetta Fersini,Enza Messina,Bing Liu
Publisher : Morgan Kaufmann
Page : 284 pages
File Size : 55,6 Mb
Release : 2016-10-06
Category : Computers
ISBN : 9780128044384

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Sentiment Analysis in Social Networks by Federico Alberto Pozzi,Elisabetta Fersini,Enza Messina,Bing Liu Pdf

The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker. Sentiment analysis has gained even more value with the advent and growth of social networking. Sentiment Analysis in Social Networks begins with an overview of the latest research trends in the field. It then discusses the sociological and psychological processes underling social network interactions. The book explores both semantic and machine learning models and methods that address context-dependent and dynamic text in online social networks, showing how social network streams pose numerous challenges due to their large-scale, short, noisy, context- dependent and dynamic nature. Further, this volume: Takes an interdisciplinary approach from a number of computing domains, including natural language processing, machine learning, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network analysis Shows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics Takes an interdisciplinary approach from a number of computing domains, including natural language processing, big data, and statistical methodologies Provides insights into opinion spamming, reasoning, and social network mining Shows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequences Serves as a one-stop reference for the state-of-the-art in social media analytics

Author : Fiona Fui-Hoon Nah,Bo Sophia Xiao
Publisher : Springer
Page : 792 pages
File Size : 54,8 Mb
Release : 2018-07-09
Category : Computers
ISBN : 9783319917160

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HCI in Business, Government, and Organizations by Fiona Fui-Hoon Nah,Bo Sophia Xiao Pdf

This book constitutes the refereed proceedings of the 5th International Conference on HCI in Business, Government and Organizations, HCIBGO 2018, held as part of the 20th International Conference on Human-Computer Interaction, HCII 2018, in Las Vegas, NV, USA. The 1171 full papers and 160 posters presented at the 14 co-located HCII 2018 conferences were carefully reviewed and selected from a total of 4346 submissions. The papers address the latest research and development efforts and highlight the human aspects of design and use of computing systems. The papers thoroughly cover the entire field of human-computer interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The papers included in this volume cover the following topics: information systems in business; electronic commerce and consumer behavior; social media and social communities in business; social innovation; and business analytics and visualization.

Author : Ruslan Mitkov
Publisher : Oxford University Press
Page : 808 pages
File Size : 43,9 Mb
Release : 2004
Category : Computers
ISBN : 9780199276349

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The Oxford Handbook of Computational Linguistics by Ruslan Mitkov Pdf

This handbook of computational linguistics, written for academics, graduate students and researchers, provides a state-of-the-art reference to one of the most active and productive fields in linguistics.

Author : Agrawal, Rashmi,Gupta, Neha
Publisher : IGI Global
Page : 346 pages
File Size : 43,7 Mb
Release : 2018-09-07
Category : Computers
ISBN : 9781522561187

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Extracting Knowledge From Opinion Mining by Agrawal, Rashmi,Gupta, Neha Pdf

Data mining techniques are commonly used to extract meaningful information from the web, such as data from web documents, website usage logs, and hyperlinks. Building on this, modern organizations are focusing on running and improving their business methods and returns by using opinion mining. Extracting Knowledge From Opinion Mining is an essential resource that presents detailed information on web mining, business intelligence through opinion mining, and how to effectively use knowledge retrieved through mining operations. While highlighting relevant topics, including the differences between ontology-based opinion mining and feature-based opinion mining, this book is an ideal reference source for information technology professionals within research or business settings, graduate and post-graduate students, as well as scholars.

Author : Chung-Chi Chen,Hen-Hsen Huang,Hsin-Hsi Chen,Xinxi Chen
Publisher : Springer Nature
Page : 102 pages
File Size : 52,8 Mb
Release : 2021
Category : Application software
ISBN : 9789811628818

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From Opinion Mining to Financial Argument Mining by Chung-Chi Chen,Hen-Hsen Huang,Hsin-Hsi Chen,Xinxi Chen Pdf

Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. These works indicate the trend toward fine-grained opinion mining in the financial domain. When expressing opinions in finance, terms like bullish/bearish often spring to mind. However, the market sentiment of the financial instrument is just one type of opinion in the financial industry. Like other industries such as manufacturing and textiles, the financial industry also has a large number of products. Financial services are also a major business for many financial companies, especially in the context of the recent FinTech trend. For instance, many commercial banks focus on loans and credit cards. Although there are a variety of issues that could be explored in the financial domain, most researchers in the AI and NLP communities only focus on the market sentiment of the stock or foreign exchange. This open access book addresses several research issues that can broaden the research topics in the AI community. It also provides an overview of the status quo in fine-grained financial opinion mining to offer insights into the futures goals. For a better understanding of the past and the current research, it also discusses the components of financial opinions one-by-one with the related works and highlights some possible research avenues, providing a research agenda with both micro- and macro-views toward financial opinions.

Author : Darja Fišer,Jakob Lenardič
Publisher : Unknown
Page : 6 pages
File Size : 53,7 Mb
Release : 2020
Category : Electronic
ISBN : OCLC:1303262881

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Overview of Tools for Sentiment Analysis and Opinion Mining by Darja Fišer,Jakob Lenardič Pdf

Author : Charu C. Aggarwal,ChengXiang Zhai
Publisher : Springer Science & Business Media
Page : 524 pages
File Size : 44,9 Mb
Release : 2012-02-03
Category : Computers
ISBN : 9781461432234

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Mining Text Data by Charu C. Aggarwal,ChengXiang Zhai Pdf

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

Author : Erik Cambria,Dipankar Das,Sivaji Bandyopadhyay,Antonio Feraco
Publisher : Springer
Page : 199 pages
File Size : 46,6 Mb
Release : 2017-04-07
Category : Medical
ISBN : 9783319553948

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A Practical Guide to Sentiment Analysis by Erik Cambria,Dipankar Das,Sivaji Bandyopadhyay,Antonio Feraco Pdf

Sentiment analysis research has been started long back and recently it is one of the demanding research topics. Research activities on Sentiment Analysis in natural language texts and other media are gaining ground with full swing. But, till date, no concise set of factors has been yet defined that really affects how writers’ sentiment i.e., broadly human sentiment is expressed, perceived, recognized, processed, and interpreted in natural languages. The existing reported solutions or the available systems are still far from perfect or fail to meet the satisfaction level of the end users. The reasons may be that there are dozens of conceptual rules that govern sentiment and even there are possibly unlimited clues that can convey these concepts from realization to practical implementation. Therefore, the main aim of this book is to provide a feasible research platform to our ambitious researchers towards developing the practical solutions that will be indeed beneficial for our society, business and future researches as well.

Author : Bilal Abu-Salih,Pornpit Wongthongtham,Dengya Zhu,Kit Yan Chan,Amit Rudra
Publisher : Springer Nature
Page : 218 pages
File Size : 40,9 Mb
Release : 2021-03-10
Category : Business & Economics
ISBN : 9789813366527

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Social Big Data Analytics by Bilal Abu-Salih,Pornpit Wongthongtham,Dengya Zhu,Kit Yan Chan,Amit Rudra Pdf

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.