Handbook of Computational Social Science, Volume 2

Uwe Engel is Professor at the University of Bremen, Germany, where he held a chair in sociology from 2000 to 2020. From 2008 to 2013, Dr. Engel coordinated the Priority Programme on “Survey Methodology” of the German Research Foundation. His current research focuses on data science, human-robot interaction, and opinion dynamics. Anabel Quan-Haase is Professor of Sociology and Information and Media Studies at Western University and Director of the SocioDigital Media Lab, London, Canada. Her research interests include social media, social networks, life course, social capital, computational social science, and digital inequality/inclusion. Sunny Xun Liu is a research scientist at Stanford Social Media Lab, USA. Her research focuses on the social and psychological effects of social media and AI, social media and well-being, and how the design of social robots impact psychological perceptions. Lars Lyberg was Head of the Research and Development Department at Statistics Sweden and Professor at Stockholm University. He was an elected member of the International Statistical Institute. In 2018, he received the AAPOR Award for Exceptionally Distinguished Achievement.

Preface






Introduction to the Handbook of Computational Social Science
Uwe Engel, Anabel Quan-Haase, Sunny Xun Liu and Lars Lyberg

Section I. Data in CSS: Collection, Management, and Cleaning




A Brief History of APIs: Limitations and Opportunities for Online Research
Jakob Jünger




Application Programming Interfaces and Web Data For Social Research
Dominic Nyhuis




Web Data Mining: Collecting Textual Data from Web Pages Using R
Stefan Bosse, Lena Dahlhaus and Uwe Engel




Analyzing Data Streams for Social Scientists
Lianne Ippel, Maurits Kaptein and Jeroen Vermunt




Handling Missing Data in Large Data Bases
Martin Spiess and Thomas Augustin




A Primer on Probabilistic Record Linkage


Ted Enamorado




Reproducibility and Principled Data Processing
John McLevey, Pierson Browne and Tyler Crick

Section II. Data Quality in CSS Research




Applying a Total Error Framework for Digital Traces to Social Media Research
Indira Sen, Fabian Flöck, Katrin Weller, Bernd Weiß and Claudia Wagner




Crowdsourcing in Observational and Experimental Research
Camilla Zallot, Gabriele Paolacci, Jesse Chandler and Itay Sisso




Inference from Probability and Nonprobability Samples
Rebecca Andridge and Richard Valliant




Challenges of Online Non-Probability Surveys
Jelke Bethlehem

Section III. Statistical Modelling and Simulation




Large-scale Agent-based Simulation and Crowd Sensing with Mobile Agents
Stefan Bosse




Agent-based Modelling for Cultural Networks: Tagging by Artificial Intelligent Cultural Agents
Fernando Sancho-Caparrini and Juan Luis Suárez




Using Subgroup Discovery and Latent Growth Curve Modeling to Identify Unusual Developmental Trajectories
Axel Mayer, Christoph Kiefer, Benedikt Langenberg and Florian Lemmerich




Disaggregation via Gaussian Regression for Robust Analysis of Heterogeneous Data
Nazanin Alipourfard, Keith Burghardt and Kristina Lerman

Section IV: Machine Learning Methods




Machine Learning Methods for Computational Social Science
Richard D. De Veaux and Adam Eck




Principal Component Analysis
Andreas Pöge and Jost Reinecke




Unsupervised Methods: Clustering Methods
Johann Bacher, Andreas Pöge and Knut Wenzig




Text Mining and Topic Modeling
Raphael H. Heiberger and Sebastian Munoz-Najar Galvez




From Frequency Counts to Contextualized Word Embeddings: The Saussurean Turn in Automatic Content Analysis
Gregor Wiedemann and Cornelia Fedtke




Automated Video Analysis for Social Science Research

Dominic Nyhuis, Tobias Ringwald, Oliver Rittmann, Thomas Gschwend and Rainer Stiefelhagen