Social Media Analytics For User Behavior Modeling
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Social Media Analytics For User Behavior Modeling
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Author : Arun Reddy Nelakurthi
language : en
Publisher: CRC Press
Release Date : 2020-01-21
Social Media Analytics For User Behavior Modeling written by Arun Reddy Nelakurthi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-21 with Computers categories.
In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.
Trends In Social Network Analysis
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Author : Rokia Missaoui
language : en
Publisher: Springer
Release Date : 2017-04-29
Trends In Social Network Analysis written by Rokia Missaoui and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-29 with Computers categories.
The book collects contributions from experts worldwide addressing recent scholarship in social network analysis such as influence spread, link prediction, dynamic network biclustering, and delurking. It covers both new topics and new solutions to known problems. The contributions rely on established methods and techniques in graph theory, machine learning, stochastic modelling, user behavior analysis and natural language processing, just to name a few. This text provides an understanding of using such methods and techniques in order to manage practical problems and situations. Trends in Social Network Analysis: Information Propagation, User Behavior Modelling, Forecasting, and Vulnerability Assessment appeals to students, researchers, and professionals working in the field.
Social Media Analytics For User Behavior Modeling
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Author : Arun Reddy Nelakurthi
language : en
Publisher: CRC Press
Release Date : 2020-01-29
Social Media Analytics For User Behavior Modeling written by Arun Reddy Nelakurthi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-29 with Computers categories.
In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.
Social Media Analytics For User Behavior Modeling
DOWNLOAD
Author : Arun Reddy Nelakurthi
language : en
Publisher: CRC Press
Release Date : 2020-01-21
Social Media Analytics For User Behavior Modeling written by Arun Reddy Nelakurthi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-21 with Computers categories.
Winner of the "Outstanding Academic Title" recognition by Choice for the 2020 OAT Awards. The Choice OAT Award represents the highest caliber of scholarly titles that have been reviewed by Choice and conveys the extraordinary recognition of the academic community. In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.
Social Networking And Community Behavior Modeling Qualitative And Quantitative Measures
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Author : Safar, Maytham
language : en
Publisher: IGI Global
Release Date : 2011-12-31
Social Networking And Community Behavior Modeling Qualitative And Quantitative Measures written by Safar, Maytham and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-12-31 with Computers categories.
Social Networking and Community Behavior Modeling: Qualitative and Quantitative Measures provides a clear and consolidated view of current social network models. This work explores new methods for modeling, characterizing, and constructing social networks. Chapters contained in this book study critical security issues confronting social networking, the emergence of new mobile social networking devices and applications, network robustness, and how social networks impact the business aspects of organizations.
Putting Social Media And Networking Data In Practice For Education Planning Prediction And Recommendation
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Author : Mehmet Kaya
language : en
Publisher: Springer Nature
Release Date : 2019-12-27
Putting Social Media And Networking Data In Practice For Education Planning Prediction And Recommendation written by Mehmet Kaya and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-27 with Science categories.
This book focusses on recommendation, behavior, and anomaly, among of social media analysis. First, recommendation is vital for a variety of applications to narrow down the search space and to better guide people towards educated and personalized alternatives. In this context, the book covers supporting students, food venue, friend and paper recommendation to demonstrate the power of social media data analysis. Secondly, this book treats behavior analysis and understanding as important for a variety of applications, including inspiring behavior from discussion platforms, determining user choices, detecting following patterns, crowd behavior modeling for emergency evacuation, tracking community structure, etc. Third, fraud and anomaly detection have been well tackled based on social media analysis. This has is illustrated in this book by identifying anomalous nodes in a network, chasing undetected fraud processes, discovering hidden knowledge, detecting clickbait, etc. With this wide coverage, the book forms a good source for practitioners and researchers, including instructors and students.
Social Media Modeling And Computing
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Author : Steven C.H. Hoi
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-22
Social Media Modeling And Computing written by Steven C.H. Hoi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-22 with Computers categories.
This timely text/reference presents the latest advances in various aspects of social media modeling and social media computing research. Gathering together superb research from a range of established international conferences and workshops, the editors coherently organize and present each of the topics in relation to the basic principles and practices of social media modeling and computing. Individual chapters can be also be used as self-contained references on the material covered. Topics and features: presents contributions from an international selection of preeminent experts in the field; discusses topics on social-media content analysis; examines social-media system design and analysis, and visual analytic tools for event analysis; investigates access control for privacy and security issues in social networks; describes emerging applications of social media, for music recommendation, automatic image annotation, and the analysis and improvement of photo-books.
Social Media Data Mining And Analytics
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Author : Gabor Szabo
language : en
Publisher: John Wiley & Sons
Release Date : 2018-09-19
Social Media Data Mining And Analytics written by Gabor Szabo and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-19 with Computers categories.
Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.
Social Media Analytics And Practical Applications
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Author : Subodha Kumar
language : en
Publisher: CRC Press
Release Date : 2021-12-30
Social Media Analytics And Practical Applications written by Subodha Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-30 with Technology & Engineering categories.
Social Media Analytics and Practical Applications: The Change to the Competition Landscape provides a framework that allows you to understand and analyze the impact of social media in various industries. It illustrates how social media analytics can help firms build transformational strategies and cope with the challenges of social media technology. By focusing on the relationship between social media and other technology models, such as wisdom of crowds, healthcare, fintech and blockchain, machine learning methods, and 5G, this book is able to provide applications used to understand and analyze the impact of social media. Various industries are called out and illustrate how social media analytics can help firms build transformational strategies and at the same time cope with the challenges that are part of the landscape. The book discusses how social media is a driving force in shaping consumer behavior and spurring innovations by embracing and directly engaging with consumers on social media platforms. By closely reflecting on emerging practices, the book shows how to take advantage of recent advancements and how business operations are being revolutionized. Social Media Analytics and Practical Applications is written for academicians and professionals involved in social media and social media analytics.
Learning Social Media Analytics With R
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Author : Raghav Bali
language : en
Publisher:
Release Date : 2017-05-26
Learning Social Media Analytics With R written by Raghav Bali and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-26 with Computers categories.
Tap into the realm of social media and unleash the power of analytics for data-driven insights using RAbout 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 such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering.Who This Book Is ForIt is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise.What You Will Learn* Learn how to tap into data from diverse social media platforms using the R ecosystem* Use social media data to formulate and solve real-world problems* Analyze user social networks and communities using concepts from graph theory and network analysis* Learn to detect opinion and sentiment, extract themes, topics, and trends from unstructured noisy text data from diverse social media channels* Understand the art of representing actionable insights with effective visualizations* Analyze data from major social media channels such as Twitter, Facebook, Flickr, Foursquare, Github, StackExchange, and so on* Learn to leverage popular R packages such as ggplot2, topicmodels, caret, e1071, tm, wordcloud, twittR, Rfacebook, dplyr, reshape2, and many moreIn DetailThe Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how analytics can be leveraged to derive insights from it. This data can be analyzed to gain valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers frame business problems and solve them using social data.The book will also cover several practical real-world use cases on social media using R and its advanced packages to utilize data science methodologies such as sentiment analysis, topic modeling, text summarization, recommendation systems, social network analysis, classification, and clustering. This will enable readers to learn different hands-on approaches to obtain data from diverse social media sources such as Twitter and Facebook. It will also show readers how to establish detailed workflows to process, visualize, and analyze data to transform social data into actionable insights.Style and approachThis book follows a step-by-step approach with detailed strategies for understanding, extracting, analyzing, visualizing, and modeling data from several major social network platforms such as Facebook, Twitter, Foursquare, Flickr, Github, and StackExchange. The chapters cover several real-world use cases and leverage data science, machine learning, network analysis, and graph theory concepts along with the R ecosystem, including popular packages such as ggplot2, caret,dplyr, topicmodels, tm, and so on.