in Regression Kaufman173 An Introduction to Exponential Random Graph Modeling Harris
174 Introduction to Time Series Analysis Pickup
175 Factorial Survey Experiments Auspurg/Hinz
176 Introduction to Power Analysis: Two-Group Studies Hedberg
177 Linear Regression: A Mathematical Introduction Gujarati
178 Propensity Score Methods and Applications Bai/Clark
179 Multilevel Structural Equation Modeling Silva/Bosancianu/Littvay
180 Gathering Social Network Data adams
Sara Miller McCune founded SAGE Publishing in 1965 to support the dissemination of usable knowledge and educate a global community. SAGE publishes more than 1000 journals and over 800 new books each year, spanning a wide range of subject areas. Our growing selection of library products includes archives, data, case studies and video. SAGE remains majority owned by our founder and after her lifetime will become owned by a charitable trust that secures the company’s continued independence.
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GATHERING SOCIAL NETWORK DATA
jimi adams
University of Colorado Denver
Copyright © 2020 by SAGE Publications, Inc.
All rights reserved. Except as permitted by U.S. copyright law, no part of this work may be reproduced or distributed in any form or by any means, or stored in a database or retrieval system, without permission in writing from the publisher.
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Names: adams, jimi, author.
Title: Gathering social network data / jimi adams, University of Colorado Denver.
Description: 1 Edition. | Thousand Oaks : SAGE Publications, [2019] | Includes bibliographical references and index.
Identifiers: LCCN 2019007277 | ISBN 9781544321462 (pbk. : alk. paper)
Subjects: LCSH: Social networks.
Classification: LCC HM741 .A33 2019 | DDC 302.3-dc23 LC record available at https://lccn.loc.gov/2019007277
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Series Editor’s Introduction
It is with great pleasure that I introduce Gathering Social Network Data, by jimi adams. This new volume fills a gap in the QASS series as well as in the literature more generally. There are several excellent texts describing social network analysis, including the one by David Knoke and Song Yang (No. 154) in this series. However, there is no text discussing methods for designing, collecting, and evaluating the data that are the subject of these analytic techniques. Such a text is urgently needed given the impressive growth in social networks research.
An expert on social networks, adams drew on his extensive experience teaching these methods to design a QASS volume that appeals to readers at all levels. For novices, adams introduces topics in a time-tested and systematic way, is careful to define terms (both in the text and in a glossary), and illustrates his points with lots of examples. The volume could serve as a useful supplement in an advanced undergraduate course or graduate seminar. For experts, he explores technicalities and points to current debates in the literature through extensive footnoting. Researchers already well established in the field will also benefit from its cogent discussion of issues surrounding the design, collection, and assessment of social network data.
As adams explains in the preface, the volume focuses on principles, with the goal of providing readers the tools needed to develop their own approach to gathering social network data. Chapter 1 introduces basic concepts, describes theoretical perspectives, and reviews types of ties and the kinds of questions of interest in social research. Chapter 2 focuses on three considerations that must be addressed in any network study: tie measurement (name generators, name interpreters, resource generators), sampling design (ego based, complete, and partial network designs), and inclusion and exclusion criteria (i.e., boundary specification). The ordering of the topics in this chapter is reflective of adams’s own teaching strategy and what has worked best over years of experience. Chapter 3 addresses modes of social network data collection, distinguishing between active and passive approaches. Chapters 1 through 3 are the core of the volume.
