This book provides a new perspective on book history, with essays from leading scholars showing how communities of writers, publishers and readers across early modern Europe shaped the consumption of print.

Epistolary Community in Print contends that the printed letter is an inherently sociable genre ideally suited to the theorisation of community in early modern England. In manual, prose or poetic form, printed letter collections make private matters public, and in so doing reveal, first how tenuous is the divide between these two realms in the early modern period and, second, how each collection helps to constitute particular communities of readers. Consequently, as Epistolary Community details, epistolary visions of community were gendered. This book provides a genealogy of epistolary discourse beginning with an introductory discussion of Gabriel Harvey and Edmund Spenser’s Wise and Wittie Letters (1580), and opening into chapters on six printed letter collections generated at times of political change. Among the authors whose letters are examined are Angel Day, Michael Drayton, Jacques du Bosque and Margaret Cavendish. Epistolary Community identifies broad patterns that were taking shape, and constantly morphing, in English printed letters from 1580 to 1664, and then considers how the six examples of printed letters selected for discussion manipulate this generic tradition to articulate ideas of community under specific historical and political circumstances. This study makes a substantial contribution to the rapidly growing field of early modern letters, and demonstrates how the field impacts our understanding of political discourses in circulation between 1580 and 1664, early modern women’s writing, print culture and rhetoric.

Provides clear guidance on leveraging computational techniques to answer social science questions In disciplines such as political science, sociology, psychology, and media studies, the use of computational analysis is rapidly increasing. Statistical modeling, machine learning, and other computational techniques are revolutionizing the way electoral results are predicted, social sentiment is measured, consumer interest is evaluated, and much more. Computational Analysis of Communication teaches social science students and practitioners how computational methods can be used in a broad range of applications, providing discipline-relevant examples, clear explanations, and practical guidance. Assuming little or no background in data science or computer linguistics, this accessible textbook teaches readers how to use state-of-the art computational methods to perform data-driven analyses of social science issues. A cross-disciplinary team of authors—with expertise in both the social sciences and computer science—explains how to gather and clean data, manage textual, audio-visual, and network data, conduct statistical and quantitative analysis, and interpret, summarize, and visualize the results. Offered in a unique hybrid format that integrates print, ebook, and open-access online viewing, this innovative resource: Covers the essential skills for social sciences courses on big data, data visualization, text analysis, predictive analytics, and others Integrates theory, methods, and tools to provide unified approach to the subject Includes sample code in Python and links to actual research questions and cases from social science and communication studies Discusses ethical and normative issues relevant to privacy, data ownership, and reproducible social science Developed in partnership with the International Communication Association and by the editors of Computational Communication Research Computational Analysis of Communication is an invaluable textbook and reference for students taking computational methods courses in social sciences, and for professional social scientists looking to incorporate computational methods into their work.

This two-volume encyclopedia provides a thorough introduction to the wide-ranging, fast-developing field of social networking, a much-needed resource at a time when new social networks or "communities" seem to spring up on the internet every day. Social networks, or groupings of individuals tied by one or more specific types of interests or interdependencies ranging from likes and dislikes, or disease transmission to the "old boy" network or overlapping circles of friends, have been in existence for longer than services such as Facebook or YouTube; analysis of these networks emphasizes the relationships within the network . This reference resource offers comprehensive coverage of the theory and research within the social sciences that has sprung from the analysis of such groupings, with accompanying definitions, measures, and research. Featuring approximately 350 signed entries, along with approximately 40 media clips, organized alphabetically and offering cross-references and suggestions for further readings, this encyclopedia opens with a thematic Reader′s Guide in the front that groups related entries by topics. A Chronology offers the reader historical perspective on the study of social networks. This two-volume reference work is a must-have resource for libraries serving researchers interested in the various fields related to social networks.

Computational approaches offer exciting opportunities for us to do social science differently. This beginner’s guide discusses a range of computational methods and how to use them to study the problems and questions you want to research. It assumes no knowledge of programming, offering step-by-step guidance for coding in Python and drawing on examples of real data analysis to demonstrate how you can apply each approach in any discipline. The book also: Considers important principles of social scientific computing, including transparency, accountability and reproducibility. Understands the realities of completing research projects and offers advice for dealing with issues such as messy or incomplete data and systematic biases. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed. For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.