Provenance Data In Social Media
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Provenance Data In Social Media
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Author : Geoffrey Barbier
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Provenance Data In Social Media written by Geoffrey Barbier and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Computers categories.
Social media shatters the barrier to communicate anytime anywhere for people of all walks of life. The publicly available, virtually free information in social media poses a new challenge to consumers who have to discern whether a piece of information published in social media is reliable. For example, it can be difficult to understand the motivations behind a statement passed from one user to another, without knowing the person who originated the message. Additionally, false information can be propagated through social media, resulting in embarrassment or irreversible damages. Provenance data associated with a social media statement can help dispel rumors, clarify opinions, and confirm facts. However, provenance data about social media statements is not readily available to users today. Currently, providing this data to users requires changing the social media infrastructure or offering subscription services. Taking advantage of social media features, research in this nascent field spearheads the search for a way to provide provenance data to social media users, thus leveraging social media itself by mining it for the provenance data. Searching for provenance data reveals an interesting problem space requiring the development and application of new metrics in order to provide meaningful provenance data to social media users. This lecture reviews the current research on information provenance, explores exciting research opportunities to address pressing needs, and shows how data mining can enable a social media user to make informed judgements about statements published in social media. Table of Contents: Information Provenance in Social Media / Provenance Attributes / Provenance via Network Information / Provenance Data
Finding Provenance Data In Social Media
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Author : Geoffrey Barbier
language : en
Publisher:
Release Date : 2011
Finding Provenance Data In Social Media written by Geoffrey Barbier and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Data mining categories.
A statement appearing in social media provides a very significant challenge for determining the provenance of the statement. Provenance describes the origin, custody, and ownership of something. Most statements appearing in social media are not published with corresponding provenance data. However, the same characteristics that make the social media environment challenging, including the massive amounts of data available, large numbers of users, and a highly dynamic environment, provide unique and untapped opportunities for solving the provenance problem for social media. Current approaches for tracking provenance data do not scale for online social media and consequently there is a gap in provenance methodologies and technologies providing exciting research opportunities. The guiding vision is the use of social media information itself to realize a useful amount of provenance data for information in social media. This departs from traditional approaches for data provenance which rely on a central store of provenance information. The contemporary online social media environment is an enormous and constantly updated "central store" that can be mined for provenance information that is not readily made available to the average social media user. This research introduces an approach and builds a foundation aimed at realizing a provenance data capability for social media users that is not accessible today.
Provenance
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Author : Luc Moreau
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013-09-01
Provenance written by Luc Moreau and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-01 with Computers categories.
The World Wide Web is now deeply intertwined with our lives, and has become a catalyst for a data deluge, making vast amounts of data available online, at a click of a button. With Web 2.0, users are no longer passive consumers, but active publishers and curators of data. Hence, from science to food manufacturing, from data journalism to personal well-being, from social media to art, there is a strong interest in provenance, a description of what influenced an artifact, a data set, a document, a blog, or any resource on the Web and beyond. Provenance is a crucial piece of information that can help a consumer make a judgment as to whether something can be trusted. Provenance is no longer seen as a curiosity in art circles, but it is regarded as pragmatically, ethically, and methodologically crucial for our day-to-day data manipulation and curation activities on the Web. Following the recent publication of the PROV standard for provenance on the Web, which the two authors actively help shape in the Provenance Working Group at the World Wide Web Consortium, this Synthesis lecture is a hands-on introduction to PROV aimed at Web and linked data professionals. By means of recipes, illustrations, a website at www.provbook.org, and tools, it guides practitioners through a variety of issues related to provenance: how to generate provenance, publish it on the Web, make it discoverable, and how to utilize it. Equipped with this knowledge, practictioners will be in a position to develop novel applications that can bring open-ness, trust, and accountability. Table of Contents: Preface / Acknowledgments / Introduction / A Data Journalism Scenario / The PROV Ontology / Provenance Recipes / Validation, Compliance, Quality, Replay / Provenance Management / Conclusion / Bibliography / Authors' Biographies / Index
Provenance In Data Science
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Author : Leslie F. Sikos
language : en
Publisher: Springer Nature
Release Date : 2021-04-26
Provenance In Data Science written by Leslie F. Sikos and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-26 with Computers categories.
RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack maps that aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues. This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.
Furin And Inflammation
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Author : A. Majid Khatib
language : en
Publisher:
Release Date :
Furin And Inflammation written by A. Majid Khatib and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Provenance And Annotation Of Data And Processes
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Author : Marta Mattoso
language : en
Publisher: Springer
Release Date : 2016-06-03
Provenance And Annotation Of Data And Processes written by Marta Mattoso and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-03 with Computers categories.
This book constitutes the refereed proceedings of the 6th International Provenance and Annotation Workshop, IPAW 2016, held in McLean, VA, USA, in June 2016. The 12 revised full papers, 14 poster papers, and 2 demonstration papers presentedwere carefully reviewed and selected from 54 submissions. The papers feature state-of-the-art research and practice around the automatic capture, representation, and use of provenance. They are organized in topical sections on provenance capture, provenance analysis and visualization, and provenance models and applications.
Social Semantic Web Mining
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Author : Tope Omitola
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Social Semantic Web Mining written by Tope Omitola and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Mathematics categories.
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).
Encyclopedia Of Big Data
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Author : Laurie A. Schintler
language : en
Publisher: Springer
Release Date : 2022-02-23
Encyclopedia Of Big Data written by Laurie A. Schintler and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-23 with Business & Economics categories.
This encyclopedia will be an essential resource for our times, reflecting the fact that we currently are living in an expanding data-driven world. Technological advancements and other related trends are contributing to the production of an astoundingly large and exponentially increasing collection of data and information, referred to in popular vernacular as “Big Data.” Social media and crowdsourcing platforms and various applications ― “apps” ― are producing reams of information from the instantaneous transactions and input of millions and millions of people around the globe. The Internet-of-Things (IoT), which is expected to comprise tens of billions of objects by the end of this decade, is actively sensing real-time intelligence on nearly every aspect of our lives and environment. The Global Positioning System (GPS) and other location-aware technologies are producing data that is specific down to particular latitude and longitude coordinates and seconds of the day. Large-scale instruments, such as the Large Hadron Collider (LHC), are collecting massive amounts of data on our planet and even distant corners of the visible universe. Digitization is being used to convert large collections of documents from print to digital format, giving rise to large archives of unstructured data. Innovations in technology, in the areas of Cloud and molecular computing, Artificial Intelligence/Machine Learning, and Natural Language Processing (NLP), to name only a few, also are greatly expanding our capacity to store, manage, and process Big Data. In this context, the Encyclopedia of Big Data is being offered in recognition of a world that is rapidly moving from gigabytes to terabytes to petabytes and beyond. While indeed large data sets have long been around and in use in a variety of fields, the era of Big Data in which we now live departs from the past in a number of key respects and with this departure comes a fresh set of challenges and opportunities that cut across and affect multiple sectors and disciplines, and the public at large. With expanded analytical capacities at hand, Big Data is now being used for scientific inquiry and experimentation in nearly every (if not all) disciplines, from the social sciences to the humanities to the natural sciences, and more. Moreover, the use of Big Data has been well established beyond the Ivory Tower. In today’s economy, businesses simply cannot be competitive without engaging Big Data in one way or another in support of operations, management, planning, or simply basic hiring decisions. In all levels of government, Big Data is being used to engage citizens and to guide policy making in pursuit of the interests of the public and society in general. Moreover, the changing nature of Big Data also raises new issues and concerns related to, for example, privacy, liability, security, access, and even the veracity of the data itself. Given the complex issues attending Big Data, there is a real need for a reference book that covers the subject from a multi-disciplinary, cross-sectoral, comprehensive, and international perspective. The Encyclopedia of Big Data will address this need and will be the first of such reference books to do so. Featuring some 500 entries, from "Access" to "Zillow," the Encyclopedia will serve as a fundamental resource for researchers and students, for decision makers and leaders, and for business analysts and purveyors. Developed for those in academia, industry, and government, and others with a general interest in Big Data, the encyclopedia will be aimed especially at those involved in its collection, analysis, and use. Ultimately, the Encyclopedia of Big Data will provide a common platform and language covering the breadth and depth of the topic for different segments, sectors, and disciplines.
Publications Combined The Role Of Social Media In Crisis Data Collection By The Public And Private Sectors As A Strategic Asset And To Prevent Terrorism
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Author :
language : en
Publisher: Jeffrey Frank Jones
Release Date : 2018-09-07
Publications Combined The Role Of Social Media In Crisis Data Collection By The Public And Private Sectors As A Strategic Asset And To Prevent Terrorism written by and has been published by Jeffrey Frank Jones this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-07 with categories.
Over 1,800 total pages ... Included publications: Social Media and the Policy-Making Process a Traditional Novel Interaction Social Media Principles Applied to Critical Infrastructure Information Sharing Trolling New Media: Violent Extremist Groups Recruiting Through Social Media An Initial Look at the Utility of Social Media as a Foreign Policy Tool Indicators of Suicide Found on Social Networks: Phase 1 Validating the FOCUS Model Through an Analysis of Identity Fragmentation in Nigerian Social Media Providing Focus via a Social Media Exploitation Strategy Assessing the Use of Social Media in a Revolutionary Environment Social Media Integration into State-Operated Fusion Centers and Local Law Enforcement: Potential Uses and Challenges Using Social Media Tools to Enhance Tacit Knowledge Sharing Within the USMC Social Media: Strategic Asset or Operational Vulnerability? Tweeting Napoleon and Friending Clausewitz: Social Media and the Military Strategist The U.S. Military and Social Media Balancing Social Media with Operations Security (OPSEC) in the 21st Century Division Level Social Media Understanding Violence Through Social Media The Investigation of Social Media Data Thresholds for Opinion Formation The Impact of Social Media on the Nature of Conflict, and a Commander's Strategy for Social Media Provenance Data in Social Media Conflict Prediction Through Geo-Spatial Interpolation of Radicalization in Syrian Social Media Social Media Effects on Operational Art Assessing the Potential of Societal Verification by Means of New Media Army Social Media: Harnessing the Power of Networked Communications Analysis of Department of Defense Social Media Policy and Its Impact on Operational Security Social Media: Valuable Tools in Today's Operational Environment Conflict Prediction Through Geo-Spatial Interpolation of Radicalization in Syrian Social Media
Natural Language Processing For Social Media
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Author : Atefeh Farzindar
language : en
Publisher: Springer Nature
Release Date : 2015-08-31
Natural Language Processing For Social Media written by Atefeh Farzindar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-31 with Computers categories.
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 and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on Natural Language Processing (NLP) tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, business intelligence, industry, marketing, and security and defense. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, and social networking.