Sentiment Analysis in Social Networks

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

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  • Author : Federico Alberto Pozzi
  • Publisher : Morgan Kaufmann
  • Pages : 284 pages
  • ISBN : 0128044381
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKSentiment Analysis in Social Networks

Sentiment Analysis in Social Networks

Sentiment Analysis in Social Networks
  • Author : Federico Alberto Pozzi,Elisabetta Fersini,Enza Messina,Bing Liu
  • Publisher : Morgan Kaufmann
  • Release : 06 October 2016
GET THIS BOOKSentiment Analysis in Social Networks

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

Sentiment Analysis in Social Networks

Sentiment Analysis in Social Networks
  • Author : Federico Pozzi,Elisabetta Fersini,Bing Liu,Enza Messina
  • Publisher : Morgan Kaufmann Publishers
  • Release : 01 October 2016
GET THIS BOOKSentiment Analysis in Social Networks

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

Sentiment Analysis for Social Media

Sentiment Analysis for Social Media
  • Author : Carlos A. Iglesias,Antonio Moreno
  • Publisher : MDPI
  • Release : 02 April 2020
GET THIS BOOKSentiment Analysis for Social Media

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

Sentiment Analysis in the UAE Social Networks Context

Sentiment Analysis in the UAE Social Networks Context
  • Author : Hind Yousif Obaid Sahoo
  • Publisher : Unknown Publisher
  • Release : 26 January 2021
GET THIS BOOKSentiment Analysis in the UAE Social Networks Context

The main goal of this study is to evaluate the effectiveness of automated opinion and sentiment analysis in social media in the UAE's telecommunications sector context. The study also investigates the possible impact of sentiments expressed in reviews and opinions published in social media on customer decisions to use a mobile Internet package (Etisalat data plan). More specifically, the study examines the relationship between emotions and the following four important customer outcomes: satisfaction, trust, loyalty, and intention to recommend or

Social Network Analytics

Social Network Analytics
  • Author : Nilanjan Dey,Samarjeet Borah,Rosalina Babo,Amira S. Ashour
  • Publisher : Academic Press
  • Release : 16 November 2018
GET THIS BOOKSocial Network Analytics

Social Network Analytics: Computational Research Methods and Techniques focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, it includes a variety of applications from several domains, such as scientific research, and the business and industrial sectors. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, the big data analytics of social networks, multidimensional scaling,

Sentiment Analysis for Social Media

Sentiment Analysis for Social Media
  • Author : Carlos A. Iglesias,Antonio Moreno
  • Publisher : MDPI
  • Release : 02 April 2020
GET THIS BOOKSentiment Analysis for Social Media

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

Web Information Systems Engineering -- WISE 2014

Web Information Systems Engineering -- WISE 2014
  • Author : Boualem Benatallah,Azer Bestavros,Yannis Manolopoulos,Athena Vakali,Yanchun Zhang
  • Publisher : Springer
  • Release : 11 September 2014
GET THIS BOOKWeb Information Systems Engineering -- WISE 2014

This book constitutes the proceedings of the 15th International Conference on Web Information Systems Engineering, WISE 2014, held in Thessaloniki, Greece, in October 2014. The 52 full papers, 16 short and 14 poster papers, presented in the two-volume proceedings LNCS 8786 and 8787 were carefully reviewed and selected from 196 submissions. They are organized in topical sections named: Web mining, modeling and classification; Web querying and searching; Web recommendation and personalization; semantic Web; social online networks; software architectures amd platforms; Web technologies and frameworks; Web innovation and applications;

Learning Social Media Analytics with R

Learning Social Media Analytics with R
  • Author : Raghav Bali,Dipanjan Sarkar,Tushar Sharma
  • Publisher : Packt Publishing Ltd
  • Release : 26 May 2017
GET THIS BOOKLearning Social Media Analytics with R

Tap into the realm of social media and unleash the power of analytics for data-driven insights using R About This Book A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms. Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques

Data Mining for Social Network Data

Data Mining for Social Network Data
  • Author : Nasrullah Memon,Jennifer Jie Xu,David L. Hicks,Hsinchun Chen
  • Publisher : Springer Science & Business Media
  • Release : 10 June 2010
GET THIS BOOKData Mining for Social Network Data

Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on Data Mining for Social Network Data will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, activities in open for a and commercial sites as well. It will also

Sentiment Analysis and Opinion Mining

Sentiment Analysis and Opinion Mining
  • Author : Bing Liu
  • Publisher : Morgan & Claypool Publishers
  • Release : 26 January 2021
GET THIS BOOKSentiment Analysis and Opinion Mining

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

Natural Language Processing for Social Media

Natural Language Processing for Social Media
  • Author : Atefeh Farzindar,Diana Inkpen
  • Publisher : Morgan & Claypool Publishers
  • Release : 15 December 2017
GET THIS BOOKNatural Language Processing for Social Media

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