Download or read book An Application of Sentiment Analysis with Transformer Models on Online News Articles Covering the Covid 19 Pandemic written by Prakul Asthana and published by . This book was released on 2021 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Covid-19 pandemic has had a devastating impact on lives across the world, with tremendous human socio-economic costs, while exposing and exacerbating several fault lines in our society. It has also caused a rapid rise in misinformation and erosion of trust in established news outlets amid allegations of political bias and censorship. In this paper we use the processes of sentiment analysis to study the coverage of the Covid-19 pandemic in news outlets. By comparing the coverage from news sources with opposing political leanings, we quantitatively establish political bias. We also repeat this process on news articles mentioning specific topics like Masks, Social Distancing etc., to check for any bias present in the sentiment towards them. Lastly, we compare sentiment in Covid-19 news coverage in the United States, the United Kingdom and Australia to contrast the political bias in news articles on the pandemic in these three countries.
Download or read book Making Sense of Large Social Media Corpora written by Antonio Moreno-Ortiz and published by Springer Nature. This book was released on with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Using Sentiment Analysis to Craft a Narrative of the COVID 19 Pandemic from the Perspective of Social Media written by Taylor Breanna Ray and published by . This book was released on 2021 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Throughout the COVID-19 pandemic, people have turned to social media to share their experiences with the coronavirus and their feelings regarding subjects like social distancing, mask-wearing, COVID-19 vaccines, and other related topics. The publicly available nature of these social media posts provides researchers the chance to obtain a consensus on an array of issues, topics, people, and entities. For the COVID-19 pandemic, this is valuable information that can prepare communities and governing bodies for future epidemics or events of a similar magnitude. However, clearly defining such a consensus can be difficult, especially if researchers want to limit the amount of bias they introduce. The process of sentiment analysis helps to address this need by categorizing text sources into one of three distinct polarities. Namely, those polarities are often positive, neutral, and negative. While sentiment analysis can take form as a completely manual task, this becomes incredibly burdensome for projects that involve substantial amounts of data. This thesis attempts to overcome this challenge by programmatically classifying the sentiment of COVID-19 posts from 10 social media and web-based forums using a multinomial Naive Bayes classifier. The unique and contrasting qualities of the social networks being analyzed provide a robust take on the public's perception of the pandemic that has not yet been offered up to the present.
Download or read book Using Sentiment and Emotion Analysis of News Articles to Analyze the Effects of Leader s Statements on COVID 19 Spread written by Poojitha Thota and published by . This book was released on 2021 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leaders generally include government officials, politicians, etc. Their statements can highly affect people's decisions in many ways. Currently, in the pandemic situation, many statements were being passed every hour and day, which showed an impact on the spread of corona virus cases atcertain location. So, this paper proposes a supervised model to analyze the variations of COVID-19 data based upon the leader's statements passed at certain time and location. The proposed methodology consists of sentiment and emotion analysis for the leader's statements to determine the true intentions of the leader. The leader's statements are a collection of data obtained by scraping webpages of popular news channels like CNN. And the COVID-19 data has been extracted from the largest collection, which is accumulated by John Hopkins University, everyday. Then, NLP text processing techniques were used to prepare the dataset and pre-process the text, through which we obtain a labelled dataset. From this, our methodology includes analyzing the obtained dataset.
Download or read book Deep Learning Applications Volume 2 written by M. Arif Wani and published by Springer. This book was released on 2020-12-14 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.
Download or read book Computational Modeling and Data Analysis in COVID 19 Research written by Chhabi Rani Panigrahi and published by Emerging Trends in Biomedical Technologies and Health informatics. This book was released on 2023-09-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent research on the COVID-19 pandemic. It includes the analysis, implementation, usage and proposed ideas and models with architecture to handle the COVID-19 outbreak. Using advanced technologies such as AI and ML techniques for data analysis, this book will be helpful to mitigate exposure and ensure public health.
Download or read book A Sentiment Analysis of Spanish and Italian News Articles about COVID 19 written by Jordany Werzner Regalado and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Sentiment Analysis and its Application in Educational Data Mining written by Soni Sweta and published by Springer Nature. This book was released on with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Moving From COVID 19 Mathematical Models to Vaccine Design Theory Practice and Experiences written by Andrés Fraguela-Collar and published by Bentham Science Publishers. This book was released on 2022-09-05 with total page 583 pages. Available in PDF, EPUB and Kindle. Book excerpt: This compendium represents a set of guides to understanding the challenging scientific, epidemiological, clinical, social, and economic phenomenon that is represented by the COVID-19 pandemic. The book explains the mathematical modeling of COVID-19 infection, with emphasis on traditional epidemiological principles. It represents a rigorous, comprehensive and multidisciplinary approach to a complex phenomenon. The chapters take into account the knowledge arising from different disciplines (epidemiology, pathophysiology, immunology, medicine, biology, vaccine development, etc.). It also covers COVID-19 data analysis, giving the reader a perspective of statistics and data science, and includes a discussion about social and economic issues of the pandemic. Each chapter is devoted to a specific topic, and is contributed by experts in epidemiology. Because of its multidisciplinary nature, this book is intended as a reference on mathematical models and basic immunotherapy for COVID-19 for a broad community of readers, from scholars who have scientific training, to general readers who have an interest in the disease.
Download or read book New Opportunities for Sentiment Analysis and Information Processing written by Sharaff, Aakanksha and published by IGI Global. This book was released on 2021-06-25 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Sentiment Analysis and Opinion Mining written by Bing Liu and published by Springer Nature. This book was released on 2022-05-31 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Sentiment Analysis for Social Media written by Carlos A. Iglesias and published by MDPI. This book was released on 2020-04-02 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Natural Language Processing for Social Media written by Atefeh Farzindar and published by Morgan & Claypool Publishers. This book was released on 2017-12-15 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.
Download or read book Advances in Sentiment Analysis written by and published by BoD – Books on Demand. This book was released on 2024-01-10 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: This cutting-edge book brings together experts in the field to provide a multidimensional perspective on sentiment analysis, covering both foundational and advanced methodologies. Readers will gain insights into the latest natural language processing and machine learning techniques that power sentiment analysis, enabling the extraction of nuanced emotions from text. Key Features: •State-of-the-Art Techniques: Explore the most recent advancements in sentiment analysis, from deep learning approaches to sentiment lexicons and beyond. •Real-World Applications: Dive into a wide range of applications, including social media monitoring, customer feedback analysis, and sentiment-driven decision-making. •Cross-Disciplinary Insights: Understand how sentiment analysis influences and is influenced by fields such as marketing, psychology, and finance. •Ethical and Privacy Considerations: Delve into the ethical challenges and privacy concerns inherent to sentiment analysis, with discussions on responsible AI usage. •Future Directions: Get a glimpse into the future of sentiment analysis, with discussions on emerging trends and unresolved challenges. This book is an essential resource for researchers, practitioners, and students in fields like natural language processing, machine learning, and data science. Whether you’re interested in understanding customer sentiment, monitoring social media trends, or advancing the state of the art, this book will equip you with the knowledge and tools you need to navigate the complex landscape of sentiment analysis.
Download or read book Opinion Mining and Sentiment Analysis written by Bo Pang and published by Now Publishers Inc. This book was released on 2008 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.
Download or read book Artificial Intelligence for COVID 19 written by Diego Oliva and published by Springer Nature. This book was released on 2021-07-19 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a compilation of the most recent implementation of artificial intelligence methods for solving different problems generated by the COVID-19. The problems addressed came from different fields and not only from medicine. The information contained in the book explores different areas of machine and deep learning, advanced image processing, computational intelligence, IoT, robotics and automation, optimization, mathematical modeling, neural networks, information technology, big data, data processing, data mining, and likewise. Moreover, the chapters include the theory and methodologies used to provide an overview of applying these tools to the useful contribution to help to face the emerging disaster. The book is primarily intended for researchers, decision makers, practitioners, and readers interested in these subject matters. The book is useful also as rich case studies and project proposals for postgraduate courses in those specializations.
Download or read book Coronavirus News Markets and AI written by Pankaj Sharma and published by Taylor & Francis. This book was released on 2020-12-27 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Coronavirus News, Markets and AI explores the analysis of unstructured data from coronavirus-related news and the underlying sentiment during its real-time impact on the world and on global financial markets, in particular. In an age where information - both real and fake - travels in the blink of an eye and significantly alters market sentiment daily, this book is a blow by blow account of economic impact of the COVID-19 pandemic. The volume: Details how AI driven machines capture, analyse and score relevant on-ground news sentiment to analyse the dynamics of market sentiment, how markets react to good or bad news across ‘short term’ and ‘long term’; Investigates what have been the most prevalent news sentiment during the pandemic, and its linkages to crude oil prices, high profile cases, impact of local news, and even the impact of Trump’s policies; Discusses the impact on what people think and discuss, how the COVID-19 crisis differs from the Global Financial Crisis of 2008, the unprecedented disruptions in supply chains and our daily lives; Showcases how easy accessibility to big data methods, cloud computing, and computational methods and the universal applicability of these tool to any topic can help analyse extract the related news sentiment in allied fields. Accessible, nuanced and insightful, this book will be invaluable for business professionals, bankers, media professionals, traders, investors, and investment consultants. It will also be of great interest to scholars and researchers of economics, commerce, science and technology studies, computer science, media and culture studies, public policy and digital humanities.
