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Social Networks and the Semantic Web by Peter Mika Pdf
Social Networks and the Semantic Web offers valuable information to practitioners developing social-semantic software for the Web. It provides two major case studies. The first case study shows the possibilities of tracking a research community over the Web. It reveals how social network mining from the web plays an important role for obtaining large scale, dynamic network data beyond the possibilities of survey methods. The second case study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies.
Social Networks and the Semantic Web by Peter Mika Pdf
Social Networks and the Semantic Web offers valuable information to practitioners developing social-semantic software for the Web. It provides two major case studies. The first case study shows the possibilities of tracking a research community over the Web. It reveals how social network mining from the web plays an important role for obtaining large scale, dynamic network data beyond the possibilities of survey methods. The second case study highlights the role of the social context in user-generated classifications in content, such as the tagging systems known as folksonomies.
Social Networks and the Semantic Web by Peter Mika Pdf
This work provides two major case studies. The first shows the possibilities of tracking a research community over the Web, combining the information obtained from the Web with other data sources, and analyzing the results. The second study highlights the role of the social context in user-generated classifications in content.
The Social Semantic Web by John G Breslin,Alexandre Passant,Stefan Decker Pdf
The Social Web (including services such as MySpace, Flickr, last.fm, and WordPress) has captured the attention of millions of users as well as billions of dollars in investment and acquisition. Social websites, evolving around the connections between people and their objects of interest, are encountering boundaries in the areas of information integration, dissemination, reuse, portability, searchability, automation and demanding tasks like querying. The Semantic Web is an ideal platform for interlinking and performing operations on diverse person- and object-related data available from the Social Web, and has produced a variety of approaches to overcome the boundaries being experienced in Social Web application areas. After a short overview of both the Social Web and the Semantic Web, Breslin et al. describe some popular social media and social networking applications, list their strengths and limitations, and describe some applications of Semantic Web technology to address their current shortcomings by enhancing them with semantics. Across these social websites, they demonstrate a twofold approach for interconnecting the islands that are social websites with semantic technologies, and for powering semantic applications with rich community-created content. They conclude with observations on how the application of Semantic Web technologies to the Social Web is leading towards the "Social Semantic Web" (sometimes also called "Web 3.0"), forming a network of interlinked and semantically-rich content and knowledge. The book is intended for computer science professionals, researchers, and graduates interested in understanding the technologies and research issues involved in applying Semantic Web technologies to social software. Practitioners and developers interested in applications such as blogs, social networks or wikis will also learn about methods for increasing the levels of automation in these forms of Web communication.
Social Semantic Web Mining by Tope Omitola,Sebastián Ríos,John Breslin Pdf
The past ten years have seen a rapid growth in the numbers of people signing up to use Web-based social networks (hundreds of millions of new members are now joining the main services each year) with a large amount of content being shared on these networks (tens of billions of content items are shared each month). With this growth in usage and data being generated, there are many opportunities to discover the knowledge that is often inherent but somewhat hidden in these networks. Web mining techniques are being used to derive this hidden knowledge. In addition, the Semantic Web, including the Linked Data initiative to connect previously disconnected datasets, is making it possible to connect data from across various social spaces through common representations and agreed upon terms for people, content items, etc. In this book, we detail some current research being carried out to semantically represent the implicit and explicit structures on the Social Web, along with the techniques being used to elicit relevant knowledge from these structures, and we present the mechanisms that can be used to intelligently mesh these semantic representations with intelligent knowledge discovery processes. We begin this book with an overview of the origins of the Web, and then show how web intelligence can be derived from a combination of web and Social Web mining. We give an overview of the Social and Semantic Webs, followed by a description of the combined Social Semantic Web (along with some of the possibilities it affords), and the various semantic representation formats for the data created in social networks and on social media sites. Provenance and provenance mining is an important aspect here, especially when data is combined from multiple services. We will expand on the subject of provenance and especially its importance in relation to social data. We will describe extensions to social semantic vocabularies specifically designed for community mining purposes (SIOCM). In the last three chapters, we describe how the combination of web intelligence and social semantic data can be used to derive knowledge from the Social Web, starting at the community level (macro), and then moving through group mining (meso) to user profile mining (micro).
Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources by Brüggemann, Stefan Pdf
Collaborative working has been increasingly viewed as a good practice for organizations to achieve efficiency. Organizations that work well in collaboration may have access to new sources of funding, deliver new, improved, and more integrated services, make savings on shared costs, and exchange knowledge, information and expertise. Collaboration and the Semantic Web: Social Networks, Knowledge Networks and Knowledge Resources showcases cutting-edge research on the intersections of Semantic Web, collaborative work, and social media research, exploring how the resources of so-called social networking applications, which bring people together to interact and encourage sharing of personal information and ideas, can be tapped by Semantic Web techniques, making shared Web contents readable and processable for machine and intelligent applications, as well as humans. Semantic technologies have shown their potential for integrating valuable knowledge, and they are being applied to the composition of digital learning and working platforms. Integrated semantic applications, linked data, social networks, and networked digital solutions can now be used in collaborative environments and present participants with the context-aware information that they need.
Cruz-Cunha, Maria Manuela,Oliveira, Eva F.,Tavares, Antonio J.,Ferreira, Luis G.
Author : Cruz-Cunha, Maria Manuela,Oliveira, Eva F.,Tavares, Antonio J.,Ferreira, Luis G. Publisher : IGI Global Page : 1099 pages File Size : 43,8 Mb Release : 2009-05-31 Category : Computers ISBN : 9781605666518
Handbook of Research on Social Dimensions of Semantic Technologies and Web Services by Cruz-Cunha, Maria Manuela,Oliveira, Eva F.,Tavares, Antonio J.,Ferreira, Luis G. Pdf
"This book discusses the new technologies of semantic Web, transforming the way we use information and knowledge"--Provided by publisher.
A Developer’s Guide to the Semantic Web by Liyang Yu Pdf
The Semantic Web represents a vision for how to make the huge amount of information on the Web automatically processable by machines on a large scale. For this purpose, a whole suite of standards, technologies and related tools have been specified and developed over the last couple of years and they have now become the foundation for numerous new applications. A Developer’s Guide to the Semantic Web helps the reader to learn the core standards, key components and underlying concepts. It provides in-depth coverage of both the what-is and how-to aspects of the Semantic Web. From Yu’s presentation, the reader will obtain not only a solid understanding about the Semantic Web, but also learn how to combine all the pieces to build new applications on the Semantic Web. The second edition of this book not only adds detailed coverage of the latest W3C standards such as SPARQL 1.1 and RDB2RDF, it also updates the readers by following recent developments. More specifically, it includes five new chapters on schema.org and semantic markup, on Semantic Web technologies used in social networks and on new applications and projects such as data.gov and Wikidata and it also provides a complete coding example of building a search engine that supports Rich Snippets. Software developers in industry and students specializing in Web development or Semantic Web technologies will find in this book the most complete guide to this exciting field available today. Based on the step-by-step presentation of real-world projects, where the technologies and standards are applied, they will acquire the knowledge needed to design and implement state-of-the-art applications.
Handbook of Social Network Technologies and Applications by Borko Furht Pdf
Social networking is a concept that has existed for a long time; however, with the explosion of the Internet, social networking has become a tool for people to connect and communicate in ways that were impossible in the past. The recent development of Web 2.0 has provided many new applications, such as Myspace, Facebook, and LinkedIn. The purpose of Handbook of Social Network Technologies and Applications is to provide comprehensive guidelines on the current and future trends in social network technologies and applications in the field of Web-based Social Networks. This handbook includes contributions from world experts in the field of social networks from both academia and private industry. A number of crucial topics are covered including Web and software technologies and communication technologies for social networks. Web-mining techniques, visualization techniques, intelligent social networks, Semantic Web, and many other topics are covered. Standards for social networks, case studies, and a variety of applications are covered as well.
The Semantic Web: Research and Applications by Enrico Franconi,Michael Kifer,Wolfgang May Pdf
This book constitutes the refereed proceedings of the 4th European Semantic Web Conference, ESWC 2007, held in Innsbruck, Austria, in June 2007. Coverage includes semantic Web services, ontology learning, inference and mapping, social semantic Web, ontologies, personalization, foundations of the semantic Web, natural languages and ontologies, and querying and Web data models.
Revolutionizing Social Networks with Semantic Web Tools by Aamir Junaid Ahmad Pdf
Revolutionizing social networks with semantic web tools refers to the application of semantic web technologies to improve the way social networks operate. Semantic web tools allow for the creation of structured data that can be easily interpreted and processed by machines, which can greatly enhance the functionality and usefulness of social networks. One example of how semantic web tools can revolutionize social networks is through the use of linked data. Linked data is a method of interconnecting data across different sources in a standardized way, allowing for easier sharing and reuse of information. By utilizing linked data, social networks can provide users with more relevant and personalized content, and allow for more efficient searching and discovery of information. Another way semantic web tools can revolutionize social networks is through the use of ontologies. Ontologies are formal representations of concepts and their relationships to one another, which can help machines understand the meaning of data. By using ontologies, social networks can provide more accurate and targeted recommendations to users, and enable more sophisticated analysis of user behavior and preferences. Overall, the use of semantic web tools has the potential to greatly enhance the functionality and usability of social networks, leading to more personalized and efficient user experiences.
Social Web Evolution: Integrating Semantic Applications and Web 2.0 Technologies by Lytras, Miltiadis D.,Ord¢¤ez de Pablos, Patricia Pdf
"This book explores the potential of Web 2.0 and its synergies with the Semantic Web and provides state-of-the-art theoretical foundations and technological applications"--Provided by publisher.
Semantic Network Analysis in Social Sciences by Elad Segev Pdf
Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases. Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It is one of the developing, cutting-edge methods to organize, identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews. Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts.
Semantic Mining of Social Networks by Jie Tang,Juanzi Li Pdf
Online social networks have already become a bridge connecting our physical daily life with the (web-based) information space. This connection produces a huge volume of data, not only about the information itself, but also about user behavior. The ubiquity of the social Web and the wealth of social data offer us unprecedented opportunities for studying the interaction patterns among users so as to understand the dynamic mechanisms underlying different networks, something that was previously difficult to explore due to the lack of available data. In this book, we present the architecture of the research for social network mining, from a microscopic point of view. We focus on investigating several key issues in social networks. Specifically, we begin with analytics of social interactions between users. The first kinds of questions we try to answer are: What are the fundamental factors that form the different categories of social ties? How have reciprocal relationships been developed from parasocial relationships? How do connected users further form groups? Another theme addressed in this book is the study of social influence. Social influence occurs when one's opinions, emotions, or behaviors are affected by others, intentionally or unintentionally. Considerable research has been conducted to verify the existence of social influence in various networks. However, few literature studies address how to quantify the strength of influence between users from different aspects. In Chapter 4 and in [138], we have studied how to model and predict user behaviors. One fundamental problem is distinguishing the effects of different social factors such as social influence, homophily, and individual's characteristics. We introduce a probabilistic model to address this problem. Finally, we use an academic social network, ArnetMiner, as an example to demonstrate how we apply the introduced technologies for mining real social networks. In this system, we try to mine knowledge from both the informative (publication) network and the social (collaboration) network, and to understand the interaction mechanisms between the two networks. The system has been in operation since 2006 and has already attracted millions of users from more than 220 countries/regions.
Knowledge Representation in the Social Semantic Web by Katrin Weller Pdf
The main purpose of this book is to sum up the vital and highly topical research issue of knowledge representation on the Web and to discuss novel solutions by combining benefits of folksonomies and Web 2.0 approaches with ontologies and semantic technologies. The book contains an overview of knowledge representation approaches in past, present and future, introduction to ontologies, Web indexing and in first case the novel approaches of developing ontologies.
