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

Produk Detail:

  • 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

Data Mining Approaches for Big Data and Sentiment Analysis in Social Media

Data Mining Approaches for Big Data and Sentiment Analysis in Social Media
  • Author : Brij Gupta,Ahmed A. Abd El-Latif,Dragan Perakovic
  • Publisher : Unknown Publisher
  • Release : 01 July 2022
GET THIS BOOKData Mining Approaches for Big Data and Sentiment Analysis in Social Media

"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"--

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

Advances in Social Computing

Advances in Social Computing
  • Author : Sun-Ki Chai,John Salerno,Patricia L. Mabry
  • Publisher : Springer Science & Business Media
  • Release : 01 April 2010
GET THIS BOOKAdvances in Social Computing

This book constitutes the refereed proceedings of the Third International Conference on Social Computing, Behavioral Modeling, and Prediction, SBP 2010, held in Bethseda, MD, USA, in March 2010. The 26 revised full papers and 23 revised poster papers presented together with 4 invited and keynote papers were carefully reviewed and selected from 78 initial submissions. The papers cover a wide range of interesting topics such as social network analysis, modeling, machine learning and data mining, social behaviors, public health, cultural aspects, effects and search.

Handbook of Research on Emerging Trends and Applications of Machine Learning

Handbook of Research on Emerging Trends and Applications of Machine Learning
  • Author : Solanki, Arun,Kumar, Sandeep,Nayyar, Anand
  • Publisher : IGI Global
  • Release : 13 December 2019
GET THIS BOOKHandbook of Research on Emerging Trends and Applications of Machine Learning

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.

Handbook of Research on Big Data Clustering and Machine Learning

Handbook of Research on Big Data Clustering and Machine Learning
  • Author : Garcia Marquez, Fausto Pedro
  • Publisher : IGI Global
  • Release : 04 October 2019
GET THIS BOOKHandbook of Research on Big Data Clustering and Machine Learning

As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is

Machine Learning Paradigms

Machine Learning Paradigms
  • Author : George A. Tsihrintzis,Lakhmi C. Jain
  • Publisher : Springer Nature
  • Release : 23 July 2020
GET THIS BOOKMachine Learning Paradigms

At the dawn of the 4th Industrial Revolution, the field of Deep Learning (a sub-field of Artificial Intelligence and Machine Learning) is growing continuously and rapidly, developing both theoretically and towards applications in increasingly many and diverse other disciplines. The book at hand aims at exposing its reader to some of the most significant recent advances in deep learning-based technological applications and consists of an editorial note and an additional fifteen (15) chapters. All chapters in the book were invited from

State of the Art Applications of Social Network Analysis

State of the Art Applications of Social Network Analysis
  • Author : Fazli Can,Tansel Özyer,Faruk Polat
  • Publisher : Springer
  • Release : 14 May 2014
GET THIS BOOKState of the Art Applications of Social Network Analysis

Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique

ICT for Agriculture and Environment

ICT for Agriculture and Environment
  • Author : Rafael Valencia-García,Gema Alcaraz-Mármol,Javier del Cioppo-Morstadt,Néstor Vera-Lucio,Martha Bucaram-Leverone
  • Publisher : Springer
  • Release : 26 December 2018
GET THIS BOOKICT for Agriculture and Environment

This book offers a remarkable collection of chapters covering a wide range of topics related to ICT applications in agriculture and the environment. It gathers the proceedings of the 2nd International Conference on ICTs in Agronomy and Environment (CITAMA 2019), held in Guayaquil, Ecuador on January 22–25, 2019. The conference attracted a total of 27 papers, submitted by pioneering researchers from countries around the globe. Following a thorough peer-review by leading experts, only 14 papers were ultimately selected for publication. They cover a diverse range

Data Mining Approaches for Big Data and Sentiment Analysis in Social Media

Data Mining Approaches for Big Data and Sentiment Analysis in Social Media
  • Author : Gupta, Brij B.,Perakovi?, Dragan,Abd El-Latif, Ahmed A.,Gupta, Deepak
  • Publisher : IGI Global
  • Release : 31 December 2021
GET THIS BOOKData Mining Approaches for Big Data and Sentiment Analysis in Social Media

Social media sites are constantly evolving with huge amounts of scattered data or big data, which makes it difficult for researchers to trace the information flow. It is a daunting task to extract a useful piece of information from the vast unstructured big data; the disorganized structure of social media contains data in various forms such as text and videos as well as huge real-time data on which traditional analytical methods like statistical approaches fail miserably. Due to this, there

Trends and Applications in Software Engineering

Trends and Applications in Software Engineering
  • Author : Jezreel Mejia,Mirna Muñoz,Álvaro Rocha,Yadira Quiñonez,Jose Calvo-Manzano
  • Publisher : Springer
  • Release : 18 October 2017
GET THIS BOOKTrends and Applications in Software Engineering

This book includes a selection of papers from the 2017 International Conference on Software Process Improvement (CIMPS’17), presenting trends and applications in software engineering. Held from 18th to 20th October 2017 in Zacatecas, Mexico, the conference provided a global forum for researchers and practitioners to present and discuss the latest innovations, trends, results, experiences and concerns in various areas of software engineering, including but not limited to software processes, security in information and communication technology, and big data. The main topics covered

Sentiment Analysis

Sentiment Analysis
  • Author : Bing Liu
  • Publisher : Cambridge University Press
  • Release : 15 October 2020
GET THIS BOOKSentiment Analysis

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

Sentiment Analysis and Opinion Mining

Sentiment Analysis and Opinion Mining
  • Author : Bing Liu
  • Publisher : Morgan & Claypool Publishers
  • Release : 01 July 2022
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