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Social media platforms are one of the main generators of textual data where people around the world share their daily life experiences and information with online society. The social, personal, and professional lives of people on these social networking sites generate not only a huge amount of data but also open doors for researchers and academicians with numerous research opportunities. This ample amount of data needs advanced machine learning, deep learning, and intelligent tools and techniques to receive, process, and interpret the information to resolve real-life challenges and improve the online social lives of people. Advanced Applications of NLP and Deep Learning in Social Media Data bridges the gap between natural language processing (NLP), advanced machine learning, deep learning, and online social media. It hopes to build a better and safer social media space by making human language available on different social media platforms intelligible for machines with the blessings of AI. Covering topics such as machine learning-based prediction, emotion recognition, and high-dimensional text clustering, this premier reference source is an essential resource for OSN service providers, psychiatrists, psychologists, clinicians, sociologists, students and educators of higher education, librarians, researchers, and academicians.
In the age of social media dominance, a staggering amount of textual data floods our online spaces daily. While this wealth of information presents boundless opportunities for research and understanding human behavior, it also poses substantial challenges. The sheer volume of data overwhelms traditional processing methods, and harnessing its potential requires sophisticated tools. Furthermore, the need for ensuring data security and mitigating risks in the digital realm has never been more pressing. Academic scholars, researchers, and professionals grapple with these issues daily, seeking innovative solutions to unlock the true value of multimedia data while safeguarding privacy and integrity. Recent Advancements in Multimedia Data Processing and Security: Issues, Challenges, and Techniques is a groundbreaking book that serves as a beacon of light amidst the sea of data-related challenges. It offers a comprehensive solution by bridging the gap between academic research and practical applications. By delving into topics such as deep learning, emotion recognition, and high-dimensional text clustering, it equips scholars and professionals with the innovative tools and techniques they need to navigate the complex landscape of multimedia data.
In an era defined by rapid technological advancements and an increasingly interconnected world, the challenges and opportunities presented by digitalization demand a new approach. The digital world, characterized by optimized, sustainable, and digitally networked solutions, necessitates the integration of intelligence systems, machine learning, deep learning, blockchain methods, and robust cybersecurity measures. Understanding these complex challenges and adapting the synergistic utilization of cutting-edge technologies are becoming increasingly necessary. Human Impact on Security and Privacy: Network and Human Security, Social Media, and Devices provides a global perspective on current and future trends concerning the integration of intelligent systems with cybersecurity applications. It offers a comprehensive exploration of ethical considerations within the realms of security, artificial intelligence, agriculture, and data science. Covering topics such as the evolving landscape of cybersecurity, social engineering perspectives, and algorithmic transparency, this publication is particularly valuable for researchers, industry professionals, academics, and policymakers in fields such as agriculture, cybersecurity, AI, data science, computer science, and ethics.
The book highlights the role of artificial intelligence in driving innovation, productivity, and efficiency. It further covers applications of artificial intelligence for digital marketing in Industry 5.0 and discusses data security and privacy issues in artificial intelligence, risk assessments, and identification strategies. This book: Discusses the role of artificial intelligence applications for digital manufacturing in Industry 5.0 Presents blockchain methods and data-driven decision-making with autonomous transportation Covers reinforcement learning algorithm and highly predicted models for accurate data analysis in industry automation Highlights the importance of robust authentication mechanisms and access control policies to protect sensitive information, prevent unauthorized access, and enable secure interactions between humans and machines Explains attack pattern detection and prediction which play a crucial role in ensuring the security of business systems and networks It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, industrial engineering, manufacturing engineering, and production engineering.
Social media applications have emerged in the last 20 years to meet the different needs of individuals, and private sector and public organizations have not been indifferent to these technologies. Social media tools help public institutions and organizations communicate directly with citizens as well as enable two-way communication and enable citizens to participate in all stages from agenda setting to evaluation of policy processes. Central and local governments, which use innovative methods to involve citizens in this process, attach significance to the development of e-participation tools. Ensuring the participation of citizens in policy processes not only determines the wishes and priorities of citizens but also uses scarce resources effectively and efficiently. Global Perspectives on Social Media Usage Within Governments reveals the best practices of various countries regarding the use of social media by central and local governments according to public administration models. The book presents various case studies on the impact of public administration models on social media use in order to contribute to public administration and social media use. Covering topics such as climate action, knowledge behaviors, and citizen participation, this premier reference source is an essential resource for government officials, public administrators, public policy scholars, social media experts, public affairs scholars, students and educators of higher education, librarians, researchers, and academicians.
This book constitutes the workshop proceedings of the 24th International Conference on Database Systems for Advanced Applications, DASFAA 2019, held in Chiang Mai, Thailand, in April 2019. The 14 full papers presented were carefully selected and reviewed from 26 submissions to the three following workshops: the 6th International Workshop on Big Data Management and Service, BDMS 2019; the 4th International Workshop on Big Data Quality Management, BDQM 2019; and the Third International Workshop on Graph Data Management and Analysis, GDMA 2019. This volume also includes the short papers, demo papers, and tutorial papers of the main conference DASFAA 2019.
This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.
Social networking sites have transformed traditional networking into a new form, prompting researchers to consider whether social capital accrues through online networking. This edited book, titled Social Capital in the Age of Online Networking: Genesis, Manifestations, and Implications, provides current and prospective theoretical and applied understandings of this newer source of investments. Edited by Dr. Najmul Hoda, an Assistant Professor in the Department of Business Administration at the College of Business, Umm Al-Qura University, this book is an ideal resource for scholars and practitioners interested in exploring the benefits of online social capital. The book is targeted towards academic scholars and is an excellent supplementary reading material for higher education institutions. It covers a range of topics such as social capital theory in online networking, empirical findings of online social capital formation, scales to measure online social capital, and online social capital and sustainable development. The book also explores the impact of technological innovations on online social capital and the applications of online social capital in business, society, and the economy. The book's objective is to provide a comprehensive understanding of the current and prospective state of theory and applications of this phenomenon, and it will benefit researchers, government and private research institutions, business corporations, and students in various fields such as business, economics, information technology, psychology, medicine, and humanities.
In the era of the metaverse, a big challenge permeates the digital landscape—a challenge that resonates both with creators seeking to thrive in this dynamic space and policymakers attempting to navigate its uncharted territories. Creators, driven by innovation, grapple with a myriad of uncertainties in monetizing their virtual content effectively. Simultaneously, policymakers find themselves at a crossroads, caught between the rapid evolution of the virtual realm and the lack of clear regulatory guidelines. This struggle is exacerbated by the issue of cybersecurity threats that cast a shadow over the metaverse's transformative potential. It is within this context of challenges that Creator's Economy in Metaverse Platforms emerges, poised to tackle the pressing issues at the intersection of creativity, regulation, and the ever-expanding metaverse. Creator's Economy in Metaverse Platforms dissects, analyzes, and offers solutions to the multifaceted challenges prevailing in the metaverse. By addressing fundamental questions about the creator economy, the elusive concept of the metaverse economy, and the indispensable role policymakers play, the book provides a holistic understanding of the landscape. Delving into topics such as stakeholder engagement, digital asset management, and the intricacies of various monetization models, it equips readers with actionable insights. Not content with a reactive approach, the book takes a proactive stance, offering solutions to foster interoperability and create an ecosystem where creators and policymakers can mutually thrive. It envisions not just a book but a catalyst for transformative change in the metaverse.