Topic Detection and Classification in Social Networks PDF Download
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Author: Dimitrios Milioris
Publisher: Springer
ISBN: 331966414X
Category : Technology & Engineering
Languages : en
Pages : 113
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Book Description
This book provides a novel method for topic detection and classification in social networks. The book addresses several research and technical challenges that are currently being investigated by the research community, from the analysis of relations and communications between members of a community, to quality, authority, relevance and timeliness of the content, traffic prediction based on media consumption, spam detection, to security, privacy and protection of personal information. Furthermore, the book discusses innovative techniques to address those challenges and provides novel solutions based on information theory, sequence analysis and combinatorics, which are applied on real data obtained from Twitter.
Author: Dimitrios Milioris
Publisher: Springer
ISBN: 331966414X
Category : Technology & Engineering
Languages : en
Pages : 113
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Book Description
This book provides a novel method for topic detection and classification in social networks. The book addresses several research and technical challenges that are currently being investigated by the research community, from the analysis of relations and communications between members of a community, to quality, authority, relevance and timeliness of the content, traffic prediction based on media consumption, spam detection, to security, privacy and protection of personal information. Furthermore, the book discusses innovative techniques to address those challenges and provides novel solutions based on information theory, sequence analysis and combinatorics, which are applied on real data obtained from Twitter.
Author: Nitin Agarwal
Publisher: Springer
ISBN: 3319941054
Category : Social Science
Languages : en
Pages : 282
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Book Description
The contributors in this book share, exchange, and develop new concepts, ideas, principles, and methodologies in order to advance and deepen our understanding of social networks in the new generation of Information and Communication Technologies (ICT) enabled by Web 2.0, also referred to as social media, to help policy-making. This interdisciplinary work provides a platform for researchers, practitioners, and graduate students from sociology, behavioral science, computer science, psychology, cultural studies, information systems, operations research and communication to share, exchange, learn, and develop new concepts, ideas, principles, and methodologies. Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining will be of interest to researchers, practitioners, and graduate students from the various disciplines listed above. The text facilitates the dissemination of investigations of the dynamics and structure of web based social networks. The book can be used as a reference text for advanced courses on Social Network Analysis, Sociology, Communication, Organization Theory, Cyber-anthropology, Cyber-diplomacy, and Information Technology and Justice.
Author: Jalal Kawash
Publisher: Springer
ISBN: 3319510495
Category : Computers
Languages : en
Pages : 231
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Book Description
This book addresses the challenges of social network and social media analysis in terms of prediction and inference. The chapters collected here tackle these issues by proposing new analysis methods and by examining mining methods for the vast amount of social content produced. Social Networks (SNs) have become an integral part of our lives; they are used for leisure, business, government, medical, educational purposes and have attracted billions of users. The challenges that stem from this wide adoption of SNs are vast. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection. This text has applications to widely used platforms such as Twitter and Facebook and appeals to students, researchers, and professionals in the field.
Author: Hyeoncheol Lee
Publisher:
ISBN:
Category :
Languages : en
Pages : 104
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Book Description
In recent years, diverse social networks, such as Facebook, YouTube, and Twitter, have rapidly grown in size and influence, and a huge amount of data is being generated from the social networks in real time. Demands for data mining on social networks have been dramatically increasing, since analyzing the data can yield insights and understanding to real world phenomenon. However, there are a lot of challenges and difficulties with data collection, management, and analysis because of the features of the social networks' data: large, noisy, and dynamic. Therefore, this study will address the overall problems with data mining in social networks and improve existing data mining techniques. We propose an integrated data collection, management and analysis system. Furthermore, we propose specific analysis methods, such as topic classification, sentiment analysis, and seed selection algorithm to analyze social networks' data.
Author: Rokia Missaoui
Publisher: Springer
ISBN: 331912188X
Category : Computers
Languages : en
Pages : 282
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Book Description
This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edited work will appeal to researchers, practitioners and students interested in the latest developments of social network analysis.
Author: Essaid Sabir
Publisher: Springer
ISBN: 3319681796
Category : Computers
Languages : en
Pages : 676
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Book Description
This book constitutes the refereed proceedings of the Third International Symposium on Ubiquitous Networking, UNet 2017, held in Casablanca, Morocco, in May 2017. The 56 full papers presented in this volume were carefully reviewed and selected from 127 submissions. They were organized in topical sections named: context-awareness and autonomy paradigms; mobile edge networking and virtualization; ubiquitous internet of things: emerging technologies and breakthroughs; and enablers, challenges and applications.
Author: Alfredo Cuzzocrea
Publisher: Springer Nature
ISBN: 3030276295
Category : Computers
Languages : en
Pages : 414
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Book Description
This book constitutes the refereed proceedings of the 13th International Conference on Flexible Query Answering Systems, FQAS 2019, held in Amantea, Italy, in July 2019. The 27 full papers and 10 short papers presented were carefully reviewed and selected from 43 submissions. The papers present emerging research trends with a special focus on flexible querying and analytics for smart cities and smart societies in the age of big data. They are organized in the following topical sections: flexible database management and querying; ontologies and knowledge bases; social networks and social media; argumentation-based query answering; data mining and knowledge discovery; advanced flexible query answering methodologies and techniques; flexible query answering methods and techniques; flexible intelligent information-oriented and network-oriented approaches; big data veracity and soft computing; flexibility in tools; and systems and miscellanea.
Author: Stan Matwin
Publisher: Springer Nature
ISBN: 3031336178
Category : Mathematics
Languages : en
Pages : 92
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Book Description
This book provides a broad overview of the state of the art of the research in generative methods for the analysis of social media data. It especially includes two important aspects that currently gain importance in mining and modelling social media: dynamics and networks. The book is divided into five chapters and provides an extensive bibliography consisting of more than 250 papers. After a quick introduction and survey of the book in the first chapter, chapter 2 is devoted to the discussion of data models and ontologies for social network analysis. Next, chapter 3 deals with text generation and generative text models and the dangers they pose to social media and society at large. Chapter 4 then focuses on topic modelling and sentiment analysis in the context of social networks. Finally, Chapter 5 presents graph theory tools and approaches to mine and model social networks. Throughout the book, open problems, highlighting potential future directions, are clearly identified. The book aims at researchers and graduate students in social media analysis, information retrieval, and machine learning applications.
Author: Mehmet Kaya
Publisher: Springer
ISBN: 3319513672
Category : Computers
Languages : en
Pages : 248
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Book Description
This book presents the state-of-the-art in various aspects of analysis and mining of online social networks. Within the broader context of online social networks, it focuses on important and upcoming topics of social network analysis and mining such as the latest in sentiment trends research and a variety of techniques for community detection and analysis. The book collects chapters that are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2015), which was held in Paris, France in August 2015. All papers have been peer reviewed and checked carefully for overlap with the literature. The book will appeal to students and researchers in social network analysis/mining and machine learning.
Author: Jalal Kawash
Publisher: Springer
ISBN: 3319135902
Category : Computers
Languages : en
Pages : 243
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Book Description
This edited volume addresses the vast challenges of adapting Online Social Media (OSM) to developing research methods and applications. The topics cover generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, behavior detection, mining social content for common trends, identifying and ranking social content sources, building friend-comprehension tools, and many others. Each of the ten chapters tackle one or more of these issues by proposing new analysis methods or new visualization techniques, or both, for famous OSM applications such as Twitter and Facebook. This collection of contributed chapters address these challenges. Online Social Media has become part of the daily lives of hundreds of millions of users generating an immense amount of 'social content'. Addressing the challenges that stem from this wide adaptation of OSM is what makes this book a valuable contribution to the field of social networks.
