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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.
This six-volume set of LNCS 14187, 14188, 14189, 14190, 14191 and 14192 constitutes the refereed proceedings of the 17th International Conference on Document Analysis and Recognition, ICDAR 2021, held in San José, CA, USA, in August 2023. The 53 full papers were carefully reviewed and selected from 316 submissions, and are presented with 101 poster presentations. The papers are organized into the following topical sections: Graphics Recognition, Frontiers in Handwriting Recognition, Document Analysis and Recognition.
This two-volume set LNCS 14193-14194 constitutes the proceedings of International Workshops co-located with the 17th International Conference on Document Analysis and Recognition, ICDAR 2023, held in San José, CA, USA, during August 21–26, 2023. The total of 43 regular papers presented in this book were carefully selected from 60 submissions. Part I contains 22 regular papers that stem from the following workshops: ICDAR 2023 Workshop on Computational Paleography (IWCP); ICDAR 2023 Workshop on Camera-Based Document Analysis and Recognition (CBDAR); ICDAR 2023 International Workshop on Graphics Recognition (GREC); ICDAR 2023 Workshop on Automatically Domain-Adapted and Personalized Document Analysis (ADAPDA); Part II contains 21 regular papers that stem from the following workshops: ICDAR 2023 Workshop on Machine Vision and NLP for Document Analysis (VINALDO); ICDAR 2023 International Workshop on Machine Learning (WML).
Leading experts in the law of the sea assess the impact of emerging technology on ocean governance.
Given the recent and rapid changes to migration patterns and citizenship processes, this volume provides a timely, compelling, empirical and theoretical study of the gendered implications of such developments. More specifically, it draws out the multiple connections between migration and citizenship concerns and practices for women. The collection features original research that examines women's diverse im/migrant and refugee experiences and exposes how gender ideologies and practices organize migrant citizenship, in its various dimensions, at the local, national and transnational levels. The volume contributes to theoretical debates on gender, migration and citizenship and provides new insights into their interrelation. It includes rich case studies that range from the Philippines and Somalia to the Caribbean and from Australasia to Canada and Britain. Designed to have a multidisciplinary appeal, it is suitable for courses on migration, diversity, gender, race, ethnicity, law and public policy, comparative politics and international relations.
In an increasingly globalized world of collapsing economic borders and extending formal political and legal equality rights, active citizenship has the potential to expand as well as deepen. At the same time, with the rise of neo-liberalism, welfare state retrenchment, decline of state employment, re-privatization and the rising gap between rich and poor, the economic, social and political citizenship rights of certain categories of people are increasingly curtailed. This book examines the complexity of citizenship in historical and contemporary contexts. It draws on empirical research from a range of countries, contexts and approaches in addressing women and citizenship in a global/local world and covers a selection of diverse issues, both present and past, to include immigration, ethnicity, class, nationality, political and economic participation, institutions and the private and public spheres. This rich collection informs our understanding of the pitfalls and possibilities for women in the persistence and changes within the contours of citizenship.
At last, an in-depth exploration of immigrant women's experiences in the labour force, family, and broader community in Atlantic Canada. Highlighting feminist research on women and gender-based analyses, the collection focuses on the intersections of gender with race, ethnicity, and class.
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.