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| contact center sentiment analysis: Sentiment Analysis in Social Networks Federico Alberto Pozzi, Elisabetta Fersini, Enza Messina, Bing Liu, 2016-10-06 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 |
| contact center sentiment analysis: Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications Gary Miner, 2012-01-11 The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications presents a comprehensive how- to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities-- |
| contact center sentiment analysis: Sentiment Analysis Bing Liu, 2020-10-15 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. |
| contact center sentiment analysis: Text Mining and Analysis Dr. Goutam Chakraborty, Murali Pagolu, Satish Garla, 2014-11-22 Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program. |
| contact center sentiment analysis: Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines Management Association, Information Resources, 2022-06-10 The rise of internet and social media usage in the past couple of decades has presented a very useful tool for many different industries and fields to utilize. With much of the world’s population writing their opinions on various products and services in public online forums, industries can collect this data through various computational tools and methods. These tools and methods, however, are still being perfected in both collection and implementation. Sentiment analysis can be used for many different industries and for many different purposes, which could better business performance and even society. The Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines discusses the tools, methodologies, applications, and implementation of sentiment analysis across various disciplines and industries such as the pharmaceutical industry, government, and the tourism industry. It further presents emerging technologies and developments within the field of sentiment analysis and opinion mining. Covering topics such as electronic word of mouth (eWOM), public security, and user similarity, this major reference work is a comprehensive resource for computer scientists, IT professionals, AI scientists, business leaders and managers, marketers, advertising agencies, public administrators, government officials, university administrators, libraries, students and faculty of higher education, researchers, and academicians. |
| contact center sentiment analysis: Amazon Connect: Up and Running Jeff Armstrong, 2021-04-23 Explore Amazon Connect, from implementing call flows and creating AI bots to integrating artificial intelligence solutions and analyzing critical customer sentiment Key FeaturesDiscover how to integrate chat with Connect to allow organizations to reduce operations costsLeverage machine learning to perform natural language processing (NLP) for analyzing customer feedback and trendsLearn how to integrate your enterprise application with Amazon ConnectBook Description Amazon Connect is a pay-as-you-go cloud contact center solution that powers Amazon's customer contact system and provides an impressive user experience while reducing costs. Connect's scalability has been especially helpful during COVID-19, helping customers with research, remote work, and other solutions, and has driven adoption rates higher. Amazon Connect: Up and Running will help you develop a foundational understanding of Connect's capabilities and how businesses can effectively estimate the costs and risks associated with migration. Complete with hands-on tutorials, costing profiles, and real-world use cases relating to improving business operations, this easy-to-follow guide will teach you everything you need to get your call center online, interface with critical business systems, and take your customer experience to the next level. As you advance, you'll understand the benefits of using Amazon Connect and cost estimation guidelines for migration and new deployments. Later, the book guides you through creating AI bots, implementing interfaces, and leveraging machine learning for business analytics. By the end of this book, you'll be able to bring a Connect call center online with all its major components and interfaces to significantly reduce personnel overhead and provide your customers with an enhanced user experience (UX). What you will learnBecome well-versed with the capabilities and benefits of Amazon ConnectDetermine cost-effective solutions by integrating Connect with AWSCreate, modify, and connect contact flows to improve efficiencyBuild a conversational interface with Amazon LexFind out how to transfer contact records out of Connect via KinesisGather user insights and improve business operations with Amazon QuickSightAnalyze customer-agent conversations with ML speech analytics capabilitiesDiscover ways to provide superior customer service at a lower costWho this book is for This Amazon Connect book is for anyone looking to save costs and improve their customer experience through a more advanced call center using Amazon Connect and other AWS capabilities. A technical understanding of Amazon Web Services (AWS) and beginner-level business administration experience are necessary to address cost concerns and risks. |
| contact center sentiment analysis: Non-Linguistic Analysis of Call Center Conversations Sunil Kumar Kopparapu, 2014-08-02 The book focuses on the part of the audio conversation not related to language such as speaking rate (in terms of number of syllables per unit time) and emotion centric features. This text examines using non-linguistics features to infer information from phone calls to call centers. The author analyzes how the conversation happens and not what the conversation is about by audio signal processing and analysis. |
| contact center sentiment analysis: Multi-Modal Sentiment Analysis Hua Xu, 2023-11-26 The natural interaction ability between human and machine mainly involves human-machine dialogue ability, multi-modal sentiment analysis ability, human-machine cooperation ability, and so on. To enable intelligent computers to have multi-modal sentiment analysis ability, it is necessary to equip them with a strong multi-modal sentiment analysis ability during the process of human-computer interaction. This is one of the key technologies for efficient and intelligent human-computer interaction. This book focuses on the research and practical applications of multi-modal sentiment analysis for human-computer natural interaction, particularly in the areas of multi-modal information feature representation, feature fusion, and sentiment classification. Multi-modal sentiment analysis for natural interaction is a comprehensive research field that involves the integration of natural language processing, computer vision, machine learning, pattern recognition, algorithm, robot intelligent system, human-computer interaction, etc. Currently, research on multi-modal sentiment analysis in natural interaction is developing rapidly. This book can be used as a professional textbook in the fields of natural interaction, intelligent question answering (customer service), natural language processing, human-computer interaction, etc. It can also serve as an important reference book for the development of systems and products in intelligent robots, natural language processing, human-computer interaction, and related fields. |
| contact center sentiment analysis: Sentiment Analysis Bing Liu, 2015-06-04 Sentiment analysis is the computational study of people's opinions, sentiments, emotions, and attitudes. This fascinating problem is increasingly important in business and society. It offers numerous research challenges but promises insight useful to anyone interested in opinion analysis and social media analysis. This book gives a comprehensive introduction to the topic from a primarily natural-language-processing point of view to help readers understand the underlying structure of the problem and the language constructs that are commonly used to express opinions and sentiments. It covers all core areas of sentiment analysis, includes many emerging themes, such as debate analysis, intention mining, and fake-opinion detection, and presents computational methods to analyze and summarize opinions. It will be a valuable resource for researchers and practitioners in natural language processing, computer science, management sciences, and the social sciences. |
| contact center sentiment analysis: Text Mining and Analysis Dr. Goutam Chakraborty, Murali Pagolu, Satish Garla, 2014-11-22 Big data: It's unstructured, it's coming at you fast, and there's lots of it. In fact, the majority of big data is text-oriented, thanks to the proliferation of online sources such as blogs, emails, and social media. However, having big data means little if you can't leverage it with analytics. Now you can explore the large volumes of unstructured text data that your organization has collected with Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. This hands-on guide to text analytics using SAS provides detailed, step-by-step instructions and explanations on how to mine your text data for valuable insight. Through its comprehensive approach, you'll learn not just how to analyze your data, but how to collect, cleanse, organize, categorize, explore, and interpret it as well. Text Mining and Analysis also features an extensive set of case studies, so you can see examples of how the applications work with real-world data from a variety of industries. Text analytics enables you to gain insights about your customers' behaviors and sentiments. Leverage your organization's text data, and use those insights for making better business decisions with Text Mining and Analysis. This book is part of the SAS Press program. |
| contact center sentiment analysis: Deep Learning-Based Approaches for Sentiment Analysis Basant Agarwal, Richi Nayak, Namita Mittal, Srikanta Patnaik, 2020-01-24 This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field. |
| contact center sentiment analysis: Deep Data Analytics for New Product Development Walter R. Paczkowski, 2020-02-19 This book presents and develops the deep data analytics for providing the information needed for successful new product development. Deep Data Analytics for New Product Development has a simple theme: information about what customers need and want must be extracted from data to effectively guide new product decisions regarding concept development, design, pricing, and marketing. The benefits of reading this book are twofold. The first is an understanding of the stages of a new product development process from ideation through launching and tracking, each supported by information about customers. The second benefit is an understanding of the deep data analytics for extracting that information from data. These analytics, drawn from the statistics, econometrics, market research, and machine learning spaces, are developed in detail and illustrated at each stage of the process with simulated data. The stages of new product development and the supporting deep data analytics at each stage are not presented in isolation of each other, but are presented as a synergistic whole. This book is recommended reading for analysts involved in new product development. Readers with an analytical bent or who want to develop analytical expertise would also greatly benefit from reading this book, as well as students in business programs. |
| contact center sentiment analysis: Big Data Analytics Strategies for the Smart Grid Carol L. Stimmel, 2016-04-19 A comprehensive data analytics program is the only way utilities will be able to meet the challenges of modern grids with operational efficiency, while reconciling the demands of greenhouse gas legislation, and establishing a meaningful return on investment from smart grid deployments. This book addresses the requirements for applying big data technologies and approaches, including Big Data cybersecurity, to the critical infrastructure that makes up the electrical utility grid. |
| contact center sentiment analysis: Sentiment Analysis and Opinion Mining Bing Liu, 2012 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 |
| contact center sentiment analysis: Critical Conversation Analysis Hansun Zhang Waring, Nadja Tadic, 2024-05-14 This book presents the first collection of conversation analytic studies addressed exclusively to issues of inequality and injustice. It offers a broad depiction of how inequality and injustice are reproduced, resisted and transformed in our daily life; together the chapters produce a forensic analysis of how participants enact discriminatory ideologies, negotiate systemic power imbalances, and pursue social change in and through the nuances of their interactions. The authors draw on audio and video recordings of interaction in a wide range of social settings, ranging from classrooms to family dinners, and political town halls to television sitcoms. The book demonstrates the power of conversation analysis to tackle issues of social (in)justice and (in)equality and launches critical conversation analysis as a distinct empirical program dedicated to systematically investigating and promoting inclusion and equity in the minute details of everyday interaction. |
| contact center sentiment analysis: Sentiment Analysis and Knowledge Discovery in Contemporary Business Rajput, Dharmendra Singh, Thakur, Ramjeevan Singh, Basha, S. Muzamil, 2018-08-31 In the era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. However, conducting sentiment analysis on these platforms can be challenging, especially for business professionals who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference source that discusses applications of sentiment analysis as well as data mining, machine learning algorithms, and big data streams in business environments. Featuring research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers seeking current research on data collection and management to drive profit. |
| contact center sentiment analysis: Computational Linguistics and Intelligent Text Processing Alexander Gelbukh, 2013-03-12 This two-volume set, consisting of LNCS 7816 and LNCS 7817, constitutes the thoroughly refereed proceedings of the 13th International Conference on Computer Linguistics and Intelligent Processing, CICLING 2013, held on Samos, Greece, in March 2013. The total of 91 contributions presented was carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections named: general techniques; lexical resources; morphology and tokenization; syntax and named entity recognition; word sense disambiguation and coreference resolution; semantics and discourse; sentiment, polarity, subjectivity, and opinion; machine translation and multilingualism; text mining, information extraction, and information retrieval; text summarization; stylometry and text simplification; and applications. |
| contact center sentiment analysis: Service Systems Implementation Haluk Demirkan, James C. Spohrer, Vikas Krishna, 2011-02-07 Service Systems Implementation provides the latest applications and practices aimed at improving the key performance indicators of service systems, especially those related to service quality, service productivity, regulatory compliance, and sustainable service innovation. The book presents action-oriented, application-oriented, design science-oriented (artifacts building: constructs, models, methods and instantiations) and case study-oriented research with actionable results by illustrating techniques that can be employed in large scale, real world examples. The case studies will help visualize service systems along the four key dimensions of people, information, technology and value propositions which can help enable better integration between them towards higher value propositions. The chapters, written by leading experts in the field, examine a wide range of substantive issues and implementations related to service science in various industries. These contributions also showcase the application of an array of research methods, including surveys, experiments, design science, case studies and frameworks, providing the reader with insights and guidelines to assist in building their own service systems, and thus, moving toward a more favorable service customer and provider experience. Service Systems Implementation, along with its companion text, The Science of Service Systems, is designed to present multidisciplinary and multisectoral perspectives on the nature of service systems, on research and practice in service, and on the future directions to advance service science. These two volumes compose a collection of articles from those involved in the emerging area known as service science. |
| contact center sentiment analysis: Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media Keikhosrokiani, Pantea, Pourya Asl, Moussa, 2022-02-18 Opinion mining and text analytics are used widely across numerous disciplines and fields in today’s society to provide insight into people’s thoughts, feelings, and stances. This data is incredibly valuable and can be utilized for a range of purposes. As such, an in-depth look into how opinion mining and text analytics correlate with social media and literature is necessary to better understand audiences. The Handbook of Research on Opinion Mining and Text Analytics on Literary Works and Social Media introduces the use of artificial intelligence and big data analytics applied to opinion mining and text analytics on literary works and social media. It also focuses on theories, methods, and approaches in which data analysis techniques can be used to analyze data to provide a meaningful pattern. Covering a wide range of topics such as sentiment analysis and stance detection, this publication is ideal for lecturers, researchers, academicians, practitioners, and students. |
| contact center sentiment analysis: The Analytical Marketer Adele Sweetwood, 2016-09-13 How to lead the change Analytics are driving big changes, not only in what marketing departments do but in how they are organized, staffed, led, and run. Leaders are grappling with issues that range from building an analytically driven marketing organization and determining the kinds of structure and talent that are needed to leading interactions with IT, finance, and sales and creating a unified view of the customer. The Analytical Marketer provides critical insight into the changing marketing organization—digital, agile, and analytical—and the tools for reinventing it. Written by the head of global marketing for SAS, The Analytical Marketer is based on the author’s firsthand experience of transforming a marketing organization from “art” to “art and science.” Challenged and inspired by their company’s own analytics products, the SAS marketing team was forced to rethink itself in order to take advantage of the new capabilities that those tools offer the modern marketer. Key marketers and managers at SAS tell their stories alongside the author’s candid lessons learned as she led the marketing organization’s transformation. With additional examples from other leading companies, this book is a practical guide and set of best practices for creating a new marketing culture that thrives on and adds value through data and analytics. |
| contact center sentiment analysis: An Introduction to Data Science Jeffrey S. Saltz, Jeffrey M. Stanton, 2017-08-25 An Introduction to Data Science is an easy-to-read data science textbook for those with no prior coding knowledge. It features exercises at the end of each chapter, author-generated tables and visualizations, and R code examples throughout. |
| contact center sentiment analysis: AI and Analytics for Smart Cities and Service Systems Robin Qiu, Kelly Lyons, Weiwei Chen, 2021-11-11 This book showcases state-of-the-art advances in service science and related fields of research, education, and practice. It presents emerging technologies and applications in contexts ranging from healthcare, energy, finance, and information technology to transportation, sports, logistics, and public services. Regardless of its size and service, every service organization is a service system. Due to the socio-technical nature of service systems, a systems approach must be adopted in order to design, develop and deliver services aimed at meeting end users’ utilitarian and socio-psychological needs alike. Understanding services and service systems often requires combining multiple methods to consider how interactions between people, technologies, organizations and information create value under various conditions. The papers in this volume highlight a host of ways to approach these challenges in service science and are based on submissions to the 2021 INFORMS Conference on Service Science. |
| contact center sentiment analysis: AI Innovations in Service and Tourism Marketing Nadda, Vipin, Tyagi, Pankaj Kumar, Singh, Amrik, Singh, Vipin, 2024-08-01 The use of artificial intelligence (AI) in service and tourism marketing has revolutionized the industry by personalizing customer experiences and optimizing operational efficiency. AI-driven tools analyze vast amounts of data to understand customer preferences, enabling businesses to offer tailored recommendations and promotions. AI-powered marketing campaigns can adapt in real-time, ensuring messages resonate with the right audience. AI Innovations in Service and Tourism Marketing discusses cutting-edge innovations in the use of AI technologies in service and tourism marketing. It explains how to harness these technologies to enhance customer experience and drive engagement. Covering topics such as automation, chatbots, and operational efficiency, this book is an excellent resource for managers, marketing professionals, business leaders, researchers, academicians, educators, and postgraduate students. |
| contact center sentiment analysis: Business Intelligence David Loshin, 2012-11-27 Business Intelligence: The Savvy Managers Guide, Second Edition, discusses the objectives and practices for designing and deploying a business intelligence (BI) program. It looks at the basics of a BI program, from the value of information and the mechanics of planning for success to data model infrastructure, data preparation, data analysis, integration, knowledge discovery, and the actual use of discovered knowledge. Organized into 21 chapters, this book begins with an overview of the kind of knowledge that can be exposed and exploited through the use of BI. It then proceeds with a discussion of information use in the context of how value is created within an organization, how BI can improve the ways of doing business, and organizational preparedness for exploiting the results of a BI program. It also looks at some of the critical factors to be taken into account in the planning and execution of a successful BI program. In addition, the reader is introduced to considerations for developing the BI roadmap, the platforms for analysis such as data warehouses, and the concepts of business metadata. Other chapters focus on data preparation and data discovery, the business rules approach, and data mining techniques and predictive analytics. Finally, emerging technologies such as text analytics and sentiment analysis are considered. This book will be valuable to data management and BI professionals, including senior and middle-level managers, Chief Information Officers and Chief Data Officers, senior business executives and business staff members, database or software engineers, and business analysts. - Guides managers through developing, administering, or simply understanding business intelligence technology - Keeps pace with the changes in best practices, tools, methods and processes used to transform an organization's data into actionable knowledge - Contains a handy, quick-reference to technologies and terminology |
| contact center sentiment analysis: Intelligent Natural Language Processing: Trends and Applications Khaled Shaalan, Aboul Ella Hassanien, Fahmy Tolba, 2017-11-17 This book brings together scientists, researchers, practitioners, and students from academia and industry to present recent and ongoing research activities concerning the latest advances, techniques, and applications of natural language processing systems, and to promote the exchange of new ideas and lessons learned. Taken together, the chapters of this book provide a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of intelligent natural language processing. The book presents the state-of-the-art in research on natural language processing, computational linguistics, applied Arabic linguistics and related areas. New trends in natural language processing systems are rapidly emerging – and finding application in various domains including education, travel and tourism, and healthcare, among others. Many issues encountered during the development of these applications can be resolved by incorporating language technology solutions. The topics covered by the book include: Character and Speech Recognition; Morphological, Syntactic, and Semantic Processing; Information Extraction; Information Retrieval and Question Answering; Text Classification and Text Mining; Text Summarization; Sentiment Analysis; Machine Translation Building and Evaluating Linguistic Resources; and Intelligent Language Tutoring Systems. |
| contact center sentiment analysis: Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2016 Aboul Ella Hassanien, Khaled Shaalan, Tarek Gaber, Ahmad Taher Azar, M. F. Tolba, 2016-10-20 This book gathers the proceedings of the 2nd International Conference on Advanced Intelligent Systems and Informatics (AISI2016), which took place in Cairo, Egypt during October 24–26, 2016. This international interdisciplinary conference, which highlighted essential research and developments in the field of informatics and intelligent systems, was organized by the Scientific Research Group in Egypt (SRGE) and sponsored by the IEEE Computational Intelligence Society (Egypt chapter) and the IEEE Robotics and Automation Society (Egypt Chapter). The book’s content is divided into four main sections: Intelligent Language Processing, Intelligent Systems, Intelligent Robotics Systems, and Informatics. |
| contact center sentiment analysis: Enterprise AI For Dummies Zachary Jarvinen, 2020-08-25 Master the application of artificial intelligence in your enterprise with the book series trusted by millions In Enterprise AI For Dummies, author Zachary Jarvinen simplifies and explains to readers the complicated world of artificial intelligence for business. Using practical examples, concrete applications, and straightforward prose, the author breaks down the fundamental and advanced topics that form the core of business AI. Written for executives, managers, employees, consultants, and students with an interest in the business applications of artificial intelligence, Enterprise AI For Dummies demystifies the sometimes confusing topic of artificial intelligence. No longer will you lag behind your colleagues and friends when discussing the benefits of AI and business. The book includes discussions of AI applications, including: Streamlining business operations Improving decision making Increasing automation Maximizing revenue The For Dummies series makes topics understandable, and as such, this book is written in an easily understood style that's perfect for anyone who seeks an introduction to a usually unforgiving topic. |
| contact center sentiment analysis: New Challenges in Distributed Information Filtering and Retrieval Cristian Lai, Giovanni Semeraro, Eloisa Vargiu, 2012-08-10 This volume focuses on new challenges in distributed Information Filtering and Retrieval. It collects invited chapters and extended research contributions from the DART 2011 Workshop, held in Palermo (Italy), on September 2011, and co-located with the XII International Conference of the Italian Association on Artificial Intelligence. The main focus of DART was to discuss and compare suitable novel solutions based on intelligent techniques and applied to real-world applications. The chapters of this book present a comprehensive review of related works and state of the art. Authors, both practitioners and researchers, shared their results in several topics such as Multi-Agent Systems, Natural Language Processing, Automatic Advertisement, Customer Interaction Analytics, Opinion Mining. |
| contact center sentiment analysis: Proceedings of International Conference on Recent Innovations in Computing Yashwant Singh, Pradeep Kumar Singh, Maheshkumar H. Kolekar, Arpan Kumar Kar, Paulo J. Sequeira Gonçalves, 2023-05-02 This book features selected papers presented at the 5th International Conference on Recent Innovations in Computing (ICRIC 2022), held on May 13–14, 2022, at the Central University of Jammu, India, and organized by the university’s Department of Computer Science and Information Technology. The conference was hosted in association with ELTE, Hungary; Knowledge University, Erbil; Cyber Security Research Lab and many other national & international partners. The book is divided into two volumes, and it includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India. |
| contact center sentiment analysis: Advice from a Call Center Geek Thomas Laird, 2018-08-21 Advice from a Call Center Geek: Rethinking Call Center Operations is a field manual for the 21st century contact center. Practical, poignant, and funny, Tom dishes out amazing real-world advice that has made his organization successful. From culture to education to incentives, Tom addresses the key areas to make your contact center world-class!Paul HerdmanHead of Customer ExperienceNICE inContactAdvice From a Call Center Geek takes a look at a new way of running today's high end contact center. Tom Laird, the CEO of award winning Expivia Interaction Marketing, 600 seat BPO call center guides you through the process of developing a world class operation.This book will take you through the process of evaluating and changing your call center's culture, how to look beyond a resume to hire the right associates and show you how to educate for quality while maintaining high level management. Advice from a Call Center Geek will make you rethink how the call center manager of today should be looking at running their call center. |
| contact center sentiment analysis: The Customer Excellence Enterprise Wayne Simmons, Tom DeWitt, 2024-10-14 Make customer-centricity tangible, sustainable, and real by implementing structural and systemic changes to the DNA of your company. Businesses need to do more than sell to customers—they need to help them live their best lives. This superior experience is what customers expect and deserve from companies and it’s possible to deliver just that with the framework provided in The Customer Excellence Enterprise: A Playbook for Creating Customers for Life. An enlightening and pragmatic guide, The Customer Excellence Enterprise is for everyone who needs to elevate the customer experience to a fundamental revenue accelerator and value driver. With this fresh perspective on customer-centricity, companies can address the persistent disconnect between their customer-first claims and an often disappointing reality. Wayne Simmons and Tom DeWitt are practitioners and professors of customer excellence. Wayne is a leader in customer excellence and customer experience management at Pfizer, the Fortune 50 global leader in health care and life sciences. Tom is the founder of CXM@MSU, an industry-facing entity designed to advance customer experience management thought and practice, and the founder and architect of North America’s first master’s degree in Customer Experience Management (CXM) at the Broad College of Business, Michigan State University. Together, they expertly frame the complexities of consistently delivering a superior customer experience at enterprise and global scale and provide a compelling case for urgency for companies to take the journey to become a Customer Excellence Enterprise (CXE). Outlining the leadership, organizational, operational, and commercial facets essential for sustained success, The Customer Excellence Enterprise is a comprehensive playbook for any company seeking to differentiate deeply from competitors and win preferred positions in the hearts and minds of today’s discerning customers. With insights into how companies can become structurally and systemically predisposed to deliver exceptional experiences, the authors draw on real-world practice and examples from customer experience “outliers”―companies renowned for consistently improving their customers' lives. Readers will also find: Practical strategies for building a case for urgency and mobilizing all levels of the enterprise to deliver tangible results. Winning methods to build deep emotional connections that lead to lifelong customer relationships. Insights into the habits and ways of working from customer experience industry outliers. The Customer Excellence Enterprise: A Playbook for Creating Customers for Life is a must-have for the boards of directors, C-Suite executives, line of business leaders and managers, marketers, sales teams, product leaders, human resources, customer experience, operations and other customer-facing professionals tasked with answering pressing questions like, Why are exceptional customer experiences still so rare? and If customers are truly the most valuable of corporate assets, why are they consistently being treated so poorly? This book serves as an invaluable tool and urgent call to action for anyone committed to elevating how customers are viewed, treated, and valued—the keys to creating customers for life. |
| contact center sentiment analysis: Data Engineering with AWS Gareth Eagar, 2021-12-29 The missing expert-led manual for the AWS ecosystem — go from foundations to building data engineering pipelines effortlessly Purchase of the print or Kindle book includes a free eBook in the PDF format. Key Features Learn about common data architectures and modern approaches to generating value from big data Explore AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines Learn how to architect and implement data lakes and data lakehouses for big data analytics from a data lakes expert Book DescriptionWritten by a Senior Data Architect with over twenty-five years of experience in the business, Data Engineering for AWS is a book whose sole aim is to make you proficient in using the AWS ecosystem. Using a thorough and hands-on approach to data, this book will give aspiring and new data engineers a solid theoretical and practical foundation to succeed with AWS. As you progress, you’ll be taken through the services and the skills you need to architect and implement data pipelines on AWS. You'll begin by reviewing important data engineering concepts and some of the core AWS services that form a part of the data engineer's toolkit. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how the transformed data is used by various data consumers. You’ll also learn about populating data marts and data warehouses along with how a data lakehouse fits into the picture. Later, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. In the final chapters, you'll understand how the power of machine learning and artificial intelligence can be used to draw new insights from data. By the end of this AWS book, you'll be able to carry out data engineering tasks and implement a data pipeline on AWS independently.What you will learn Understand data engineering concepts and emerging technologies Ingest streaming data with Amazon Kinesis Data Firehose Optimize, denormalize, and join datasets with AWS Glue Studio Use Amazon S3 events to trigger a Lambda process to transform a file Run complex SQL queries on data lake data using Amazon Athena Load data into a Redshift data warehouse and run queries Create a visualization of your data using Amazon QuickSight Extract sentiment data from a dataset using Amazon Comprehend Who this book is for This book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts while gaining practical experience with common data engineering services on AWS will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book but it’s not a prerequisite. Familiarity with the AWS console and core services will also help you follow along. |
| contact center sentiment analysis: Digital marketing like a PRO Clo Willaerts, 2023-01-31 How do you translate your business objectives into a digital marketing strategy? What are today's best practices for content marketing, email marketing, social media and online advertising? What is the practical use for new technologies like Augmented and Virtual Reality, the Internet of Things, Artificial Intelligence and chatbots? Digital Marketing like a PRO is an easy to follow, step-by-step marketing guide that helps you maximize all digital channels. Packed with models, information and examples to help you succeed, it is free of fluff and noise so you can get to work quickly. Whether you're new to marketing or a long-time professional seeking to boost your skills, this digital marketing handbook will help you save time, energy and resources as you learn from tested industry models and best practices. |
| contact center sentiment analysis: The Applied AI and Natural Language Processing Workshop Krishna Sankar, Jeffrey Jackovich, Ruze Richards, 2020-07-27 With the help of engaging activities, learn how to leverage Amazon Web Services for building serverless intelligent applications that can process information in no time Key FeaturesLearn how to integrate Amazon's Simple Storage Services with AI and NLP projectsGet to grips with serverless computing and its applicationsCreate intelligent applications such as chatbots and image recognition modelsBook Description Are you fascinated with applications like Alexa and Siri and how they accurately process information within seconds before returning accurate results? Are you looking for a practical guide that will teach you how to build intelligent applications that can revolutionize the world of artificial intelligence? The Applied AI and NLP Workshop will take you on a practical journey where you will learn how to build artificial intelligence (AI) and natural language processing (NLP) applications with Amazon Web services (AWS). Starting with an introduction to AI and machine learning, this book will explain how Amazon S3, or Amazon Simple Storage Service, works. You'll then integrate AI with AWS to build serverless services and use Amazon's NLP service Comprehend to perform text analysis on a document. As you advance, the book will help you get to grips with topic modeling to extract and analyze common themes on a set of documents with unknown topics. You'll also work with Amazon Lex to create and customize a chatbot for task automation and use Amazon Rekognition for detecting objects, scenes, and text in images. By the end of The Applied AI and NLP Workshop, you'll be equipped with the knowledge and skills needed to build scalable intelligent applications with AWS. What you will learnGrasp the fundamentals of AI, ML, and AWSExplore the AWS command line, its interface, and its applicationsImport and export data to Amazon S3Perform topic modeling on a set of documents to analyze common themesDevelop a custom chatbot to get the latest stock market quotesCreate a personal call center and connect it to the chatbotWho this book is for If you are a machine learning enthusiast, data scientist, or programmer who wants to explore AWS's artificial intelligence and machine learning capabilities, this book is for you. Although not necessary, a basic understanding of AI and NLP will assist with grasping key topics quickly. |
| contact center sentiment analysis: The Social Media Management Handbook Robert Wollan, Nick Smith, Catherine Zhou, 2011-01-04 How do organizations manage social media effectively? Every organization wants to implement social media, but it is difficult to create processes and mange employees to make this happen. Most social media books focus on strategies for communicating with customers, but they fail to address the internal process that takes place within a business before those strategies can be implemented. This book is geared toward helping you manage every step of the process required to use social media for business. The Social Media Management Handbook provides a complete toolbox for defining and practicing a coherent social media strategy. It is a comprehensive resource for bringing together such disparate areas as IT, customer service, sales, communications, and more to meet social media goals. Wollan and Smith and their Accenture team explain policies, procedures, roles and responsibilities, metrics, strategies, incentives, and legal issues that may arise. You will learn how to: Empower employees and teams to utilize social media effectively throughout the organization Measure the ROI of social media investments and ensure appropriate business value is achieved over time Make smarter decisions, make them more quickly, and make them stick Get the most out of your social media investment and fully leverage its benefits at your company with The Social Media Management Handbook. |
| contact center sentiment analysis: Social Media, Sociality, and Survey Research Craig A. Hill, Elizabeth Dean, Joe Murphy, 2013-09-25 Provides the knowledge and tools needed for the future of survey research The survey research discipline faces unprecedented challenges, such as falling response rates, inadequate sampling frames, and antiquated approaches and tools. Addressing this changing landscape, Social Media, Sociality, and Survey Research introduces readers to a multitude of new techniques in data collection in one of the fastest developing areas of survey research. The book is organized around the central idea of a sociality hierarchy in social media interactions, comprised of three levels: broadcast, conversational, and community based. Social Media, Sociality, and Survey Research offers balanced coverage of the theory and practice of traditional survey research, while providing a conceptual framework for the opportunities social media platforms allow. Demonstrating varying perspectives and approaches to working with social media, the book features: New ways to approach data collection using platforms such as Facebook and Twitter Alternate methods for reaching out to interview subjects Design features that encourage participation with engaging, interactive surveys Social Media, Sociality, and Survey Research is an important resource for survey researchers, market researchers, and practitioners who collect and analyze data in order to identify trends and draw reliable conclusions in the areas of business, sociology, psychology, and population studies. The book is also a useful text for upper-undergraduate and graduate-level courses on survey methodology and market research. |
| contact center sentiment analysis: Sentiment Analysis for Social Media Carlos A. Iglesias, Antonio Moreno, 2020-04-02 Sentiment analysis is a branch of natural language processing concerned with the study of the intensity of the emotions expressed in a piece of text. The automated analysis of the multitude of messages delivered through social media is one of the hottest research fields, both in academy and in industry, due to its extremely high potential applicability in many different domains. This Special Issue describes both technological contributions to the field, mostly based on deep learning techniques, and specific applications in areas like health insurance, gender classification, recommender systems, and cyber aggression detection. |
| contact center sentiment analysis: New Opportunities for Sentiment Analysis and Information Processing Sharaff, Aakanksha, Sinha, G. R., Bhatia, Surbhi, 2021-06-25 Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts. New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students. |
| contact center sentiment analysis: Real-World Data Mining Dursun Delen, 2014-12-16 Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials. Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based. |
| contact center sentiment analysis: Introduction to Statistical and Machine Learning Methods for Data Science Carlos Andre Reis Pinheiro, Mike Patetta, 2021-08-06 Boost your understanding of data science techniques to solve real-world problems Data science is an exciting, interdisciplinary field that extracts insights from data to solve business problems. This book introduces common data science techniques and methods and shows you how to apply them in real-world case studies. From data preparation and exploration to model assessment and deployment, this book describes every stage of the analytics life cycle, including a comprehensive overview of unsupervised and supervised machine learning techniques. The book guides you through the necessary steps to pick the best techniques and models and then implement those models to successfully address the original business need. No software is shown in the book, and mathematical details are kept to a minimum. This allows you to develop an understanding of the fundamentals of data science, no matter what background or experience level you have. |
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