Social Network Analysis Methods For International Development

Social Network Analysis (SNA) is a promising yet underutilized tool in the international development field. SNA entails collecting and analyzing data to characterize and visualize social networks, where nodes represent network members and edges connecting nodes represent relationships or exchanges among them. SNA can help both researchers and practitioners understand the social, political, and economic relational dynamics at the heart of international development programming. It can inform program design, monitoring, and evaluation to answer questions related to where people get information; with whom goods and services are exchanged; who people value, trust, or respect; who has power and influence and who is excluded; and how these dynamics change over time. This brief advances the case for use of SNA in international development, outlines general approaches, and discusses two recently conducted case studies that illustrate its potential. It concludes with recommendations for how to increase SNA use in international development.

Incorporate social network analysis (SNA) into monitoring, evaluation, and learning processes. SNA can be conducted at various points of a project to inform program design, adaptive management, learning, and evaluation by considering network structure and network changes over time. Demystify the use of SNA. Increased use of SNA tools and clear presentation in widely read publications are needed to bring the analytic approach into the mainstream of international development. Build capacity to conduct SNA. The capacity to conduct and interpret SNA is lacking across actors in international development. Efforts by some organizations to build capacity in the community are well noted and should be built upon. Build understanding of relationships between social networks and development outcomes. SNA will be useful only to the extent it helps users understand the relationship between networks and development outcomes that matter. Establish norms for data collection and identity protection. Data about individuals and their interactions with others are inherently sensitive data. As a part of standard research ethics protocols, SNA practitioners must make carefully considered decisions about how or if to anonymize data when reporting it.

The book includes both invited and contributed chapters dealing with advanced methods and theoretical development for the analysis of social networks and applications in numerous disciplines. Some authors explore new trends related to network measures, multilevel networks and clustering on networks, while other contributions deepen the relationship among statistical methods for data mining and social network analysis. Along with the new methodological developments, the book offers interesting applications to a wide set of fields, ranging from the organizational and economic studies, collaboration and innovation, to the less usual field of poetry. In addition, the case studies are related to local context, showing how the substantive reasoning is fundamental in social network analysis. The list of authors includes both top scholars in the field of social networks and promising young researchers. All chapters passed a double blind review process followed by the guest editors. This edited volume will appeal to students, researchers and professionals.

Social network analysis is used widely in the social and behavioral sciences, as well as in economics, marketing, and industrial engineering. The social network perspective focuses on relationships among social entities and is an important addition to standard social and behavioral research, which is primarily concerned with attributes of the social units. Social Network Analysis: Methods and Applications reviews and discusses methods for the analysis of social networks with a focus on applications of these methods to many substantive examples. It is a reference book that can be used by those who want a comprehensive review of network methods, or by researchers who have gathered network data and want to find the most appropriate method by which to analyze it. It is also intended for use as a textbook as it is the first book to provide comprehensive coverage of the methodology and applications of the field.

The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many opportunities in different application domains. Forming a bridge between theory and applications makes this work appealing to both academics and practitioners as well as graduate students.

Ideas about social structure and social networks are very old. People have always believed that biological and social links among individuals are important. But it wasn't until the early 1930s that systematic research that explored the patterning of social ties linking individuals emerged. And it emerged, not once, but several times in several different social science fields and in several places. This book reviews these developments and explores the social processes that wove all these "schools" of network analysis together into a single coherent approach.

Since the publication of Herbert Spencer's Principles of Sociology in 1875, the use of social structure as a defining concept has produced a large body of creative speculations, insights, and intuitions about social life. However, writers in this tradition do not always provide the sorts of formal definitons and propositions that are the building blocks of modern social research. In its broad-ranging examination of the kind of data that form the basis for the systematic study of social structure, Research Methods in Social Network Analysis marks a significant methodological advance in network studies.As used in this volume, social structure refers to a bundle of intuitive natural language ideas and concepts about patterning in social relationships among people. In contrast, social networks is used to refer to a collection of precise analytic and methodological concepts and procedures that facilitate the collection of data and the systematic study of such patterning. Accordingly, the book's five sections are arranged to address analytical problems in a series of logically ordered stages or processes.The major contributors define the fundamental modes by which social structural phenomena are to be represented; how boundaries to a social structure are set; how the relations of a network are measured in terms of structure and content; the ways in which the relational structure of a network affects system actors; and how actors within a social network are clustered into cliques or groups. The chapters in the last section build on solutions to problems proposed in the previous sections. This highly unified approach to research design combined with a representative diversity of viewpoints makes Research Methods in Social Network Analysis a state-of-the-art volume.

This book discusses the crucial place that assumptions hold in conceptualizing, implementing, and evaluating development programs. It suggests simple ways for stakeholders and evaluators to 1) examine their assumptions about program theory and environmental conditions and 2) develop and carry out effective program monitoring and evaluation in light of those assumptions. A survey of evaluators from an international development agency reviewed the state of practice on assumptions-aware evaluation. This 2nd edition has been updated with further illustrations, case studies, and frameworks that have been researched and tested in the years since the first edition. Regardless of geography or goal, development programs and policies are fueled by a complex network of implicit ideas. Stakeholders may hold assumptions about purposes, outcomes, methodology, and the value of project evaluation and evaluators—which may or may not be shared by the evaluators. A major barrier to viable program evaluations is that development programs are based on assumptions that often are not well articulated. In designing programs, stakeholders often lack clear outlines for how implemented interventions will bring desired changes. This lack of clarity masks critical risks to program success and makes it challenging to evaluate such programs. Methods that have attempted to address this dilemma have been popularized as theory of change or other theory‐based approaches. Often, however, theory-based methods do not sufficiently clarify how program managers or evaluators should work with the assumptions inherent in the connections between the steps. The critical examination of assumptions in evaluation is essential for effective evaluations and evaluative thinking. "How does one think evaluatively? It all begins with assumptions. Systematically articulating, examining, and testing assumptions is the foundation of evaluative thinking... This book, more than any other, explains how to build a strong foundation for effective interventions and useful evaluation by rigorously working with assumptions." —Michael Quinn Patton, PhD. Author of Utilization-Focused Evaluation and co-editor of THOUGHTWORK: Thinking, Action, and the Fate of the World, USA. "This updated edition presents us with a new opportunity to delve into both the theoretical and practical aspects of paradigmatic, prescriptive, and causal assumptions. We need to learn, and apply these insights with the deep attention they deserve." —Zenda Ofir, PhD. Independent Evaluator, Richard von Weizsäcker Fellow, Robert Bosch Academy, Berlin, Germany. Honorary Professor, School of Public Leadership, Stellenbosch University, South Africa. “This thought-provoking book explains why assumptions are an essential condition within the theories and methodologies of evaluation; and how assumptions influence the ways that evaluators approach their work...It will enrich the ways that evaluators develop their models, devise their methodologies, interpret their data, and interact with their stakeholders.” —Jonny Morell, Ph.D., President, 4.669... Evaluation and Planning, Editor Emeritus, Evaluation and Program Planning