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Data mining for the social sciences
We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.
eBook
Data, now bigger and better!
\"Data is too big to be left to the data analysts! Here, Prickly Paradigm brings together five researchers whose work is deeply informed by anthropology, understood as more than a basket of ethnographic methods like participants observation and interviewing. The value of anthropology lies also in its conceptual frameworks, frameworks that are comparative as well as field-based. Kinship! Gifts! Everything old is new when the anthropological archive washes over 'big data'. Bringing together anthropology's classic debates and contemporary interventions, this book counters the future-oriented hype and speculation so characteristic of discussions regarding big data. By drawing as well on long experience in industry contexts, the contributors provide analytical provocations that can help reframe what may prove to be some of the most important shifts in technology and society in the first half of the twenty-first century\"--Back cover.
Book
Thick Big Data
The social sciences are becoming datafied. The questions that have been considered the domain of sociologists, now are answered by data scientists, operating on large datasets, and breaking with the methodological tradition for better or worse. The traditional social sciences, such as sociology or anthropology, are thus under the double threat of becoming marginalized or even irrelevant; both because of the new methods of research, which require more computational skills, and because of the increasing competition from the corporate world, which gains an additional advantage based on data access. However, sociologists and anthropologists still have some important assets, too. Unlike data scientists, they have a long history of doing qualitative research. The more quantified datasets we have, the more difficult it is to interpret them without adding layers of qualitative interpretation. Big Data needs Thick Data. This book presents the available arsenal of new tools for studying the society quantitatively, but also show the new methods of analysis from the qualitative side and encourages their combination. In shows that Big Data can and should be supplemented and interpreted through thick data, as well as cultural analysis, in a novel approach of Thick Big Data.The book is critically important for students and researchers in the social sciences to understand the possibilities of digital analysis, both in the quantitative and qualitative area, and successfully build mixed-methods approaches.
eBook
Structural equation modeling : applications using Mplus
A reference guide for applications of SEM using Mplus Structural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a reference guide. Written in non-mathematical terms, this book focuses on the conceptual and practical aspects of Structural Equation Modeling (SEM). Basic concepts and examples of various SEM models are demonstrated along with recently developed advanced methods, such as mixture modeling and model-based power analysis and sample size estimate for SEM. The statistical modeling program, Mplus, is also featured and provides researchers with a flexible tool to analyze their data with an easy-to-use interface and graphical displays of data and analysis results. Key features: Presents a useful reference guide for applications of SEM whilst systematically demonstrating various advanced SEM models, such as multi-group and mixture models using Mplus. Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes. Provides step-by-step instructions of model specification and estimation, as well as detail interpretation of Mplus results. Explores different methods for sample size estimate and statistical power analysis for SEM. By following the examples provided in this book, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book.
eBook
Deviance in social media and social cyber forensics : uncovering hidden relations using open source information (OSINF)
This book describes the methodologies and tools used to conduct social cyber forensic analysis. By applying these methodologies and tools on various events observed in the case studies contained within, their effectiveness is highlighted. They blend computational social network analysis and cyber forensic concepts and tools in order to identify and study information competitors. Through cyber forensic analysis, metadata associated with propaganda-riddled websites are extracted. This metadata assists in extracting social network information such as friends and followers along with communication network information such as networks depicting flows of information among the actors such as tweets, replies, retweets, mentions, and hyperlinks. Through computational social network analysis, the authors identify influential actors and powerful groups coordinating the disinformation campaign. A blended social cyber forensic approach allows them to study cross-media affiliations of the information competitors. For instance, narratives are framed on blogs and YouTube videos, and then Twitter and Reddit, for instance, will be used to disseminate the message. Social cyber forensic methodologies enable researchers to study the role of modern information and communication technologies (ICTs) in the evolution of information campaign and coordination. In addition to the concepts and methodologies pertaining to social cyber forensics, this book also offers a collection of resources for readers including several datasets that were collected during case studies, up-to-date reference and literature surveys in the domain, and a suite of tools that students, researchers, and practitioners alike can utilize. Most importantly, the book demands a dialogue between information science researchers, public affairs officers, and policy makers to prepare our society to deal with the lawless \"wild west\" of modern social information systems triggering debates and studies on cyber diplomacy.
Book
Causal inference : the mixtape
An accessible and contemporary introduction to the methods for determining cause and effect in the social sciences Causal inference encompasses the tools that allow social scientists to determine what causes what. Economists-who generally can't run controlled experiments to test and validate their hypotheses-apply these tools to observational data to make connections. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied, whether the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the introduction of malaria nets in developing regions on economic growth. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and Stata programming languages.
eBook
Conducting Research Surveys via E-mail and the Web
Internet-based surveys, although still in their infancy, are becomingincreasingly popular because they are believed to be faster, better,cheaper, and easier to conduct than surveys using more-traditional telephoneor mail methods. Based on evidence in the literature and real-life casestudies, this book examines the validity of those claims. The authorsdiscuss the advantages and disadvantages of using e-mail and the Web toconduct research surveys, and also offer practical suggestions for designing and implementing Internet surveys most effectively.Among other findings, the authors determined that Internet surveys may bepreferable to mail or telephone surveys when a list of e-mail addresses forthe target population is available, thus eliminating the need for mail orphone invitations to potential respondents. Internet surveys also arewell-suited for larger survey efforts and for some target populations thatare difficult to reach by traditional survey methods. Web surveys areconducted more quickly than mail or phone surveys when respondents arecontacted initially by e-mail, as is often the case when a representativepanel of respondents has been assembled in advance. And, although surveysincur virtually no coding or data-entry costs because the data are capturedelectronically, the labor costs for design and programming can be high.
eBook