Sentiment Analysis in Social Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sentiment Analysis in Social Networks write by Federico Alberto Pozzi. This book was released on 2016-10-06. Sentiment Analysis in Social Networks available in PDF, EPUB and Kindle. 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
Sentiment Analysis for Social Media
Sentiment Analysis for Social Media - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sentiment Analysis for Social Media write by Carlos A. Iglesias. This book was released on 2020-04-02. Sentiment Analysis for Social Media available in PDF, EPUB and Kindle. 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.
Data Mining Approaches for Big Data and Sentiment Analysis in Social Media
Data Mining Approaches for Big Data and Sentiment Analysis in Social Media - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Mining Approaches for Big Data and Sentiment Analysis in Social Media write by Brij Gupta. This book was released on 2021. Data Mining Approaches for Big Data and Sentiment Analysis in Social Media available in PDF, EPUB and Kindle. "This book explores the key concepts of data mining and utilizing them on online social media platforms, offering valuable insight into data mining approaches for big data and sentiment analysis in online social media and covering many important security and other aspects and current trends"--
Handbook of Research on Emerging Trends and Applications of Machine Learning
Handbook of Research on Emerging Trends and Applications of Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Research on Emerging Trends and Applications of Machine Learning write by Solanki, Arun. This book was released on 2019-12-13. Handbook of Research on Emerging Trends and Applications of Machine Learning available in PDF, EPUB and Kindle. As today’s world continues to advance, Artificial Intelligence (AI) is a field that has become a staple of technological development and led to the advancement of numerous professional industries. An application within AI that has gained attention is machine learning. Machine learning uses statistical techniques and algorithms to give computer systems the ability to understand and its popularity has circulated through many trades. Understanding this technology and its countless implementations is pivotal for scientists and researchers across the world. The Handbook of Research on Emerging Trends and Applications of Machine Learning provides a high-level understanding of various machine learning algorithms along with modern tools and techniques using Artificial Intelligence. In addition, this book explores the critical role that machine learning plays in a variety of professional fields including healthcare, business, and computer science. While highlighting topics including image processing, predictive analytics, and smart grid management, this book is ideally designed for developers, data scientists, business analysts, information architects, finance agents, healthcare professionals, researchers, retail traders, professors, and graduate students seeking current research on the benefits, implementations, and trends of machine learning.
Sentiment Analysis in Social Networks
Sentiment Analysis in Social Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sentiment Analysis in Social Networks write by Federico Pozzi. This book was released on 2016-10-01. Sentiment Analysis in Social Networks available in PDF, EPUB and Kindle. 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 methodologiesProvides insights into opinion spamming, reasoning, and social network analysisShows how to apply sentiment analysis tools for a particular application and domain, and how to get the best results for understanding the consequencesServes 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 methodologiesProvides insights into opinion spamming, reasoning, and social network miningShows how to apply opinion mining tools for a particular application and domain, and how to get the best results for understanding the consequencesServes as a one-stop reference for the state-of-the-art in social media analytics
