Case Studies

Using Controlled and Field Experiments to Create and Test Digital News Quizzes

This case study examines controlled and field experiments used to test the effects of news quizzes. The methods, and their limitations, are described, along with the decisions that the researchers made related to the participants, stimuli, measures, and research partner used in the project. The researchers also provide practical details about how they collaborated with a survey research firm, built a relationship with a newsroom, and statistically analysed the data. The case concludes by suggesting some general lessons learned: social science research is collaborative; multi-methodological approaches help build confidence in research findings; and research that builds bridges between academics and practitioners is important.

1: Under what circumstances might it be beneficial for researchers to consider conducting a field experiment?

2: What are the differences between controlled experiments and field experiments?


A Longitudinal Study of Stability and Change in Time Perspective

This case discusses longitudinal research, focusing on various definitions of stability and change to investigate temporal aspects, in a psychological construct called time perspective. To investigate stability and change, a number of quantitative approaches were adopted, including latent growth modeling, correlational analysis, repeated analysis of variance, and the reliable change index. Longitudinal research presents significant methodological and design challenges, such as creating fit between the theoretical framework adopted in the research with the chosen longitudinal design –  timing and spacing of observations, measures, the unit of analysis, the sample size –  and the statistical approaches selected to answer the research questions.

1: Explain the importance of structural stability to longitudinal research findings.

2: Why is data screening important in longitudinal research?


The Use of ‘Big Data’ for Social Sciences Research: An Application to Corruption Research

This methodology case study describes big data analysis with reference to the example of a research project looking into high-level corruption in public procurement in Central and Eastern Europe. This project collects hundreds of thousands of official procurement announcements available online, such as contract award announcements. As there is no readily available database of public procurement announcements in any of the Central and Eastern European countries, it uses computer algorithms to download announcement texts from which useful information, ‘variables’, are then extracted. The so-developed new database sheds new light on the process of corruption in public procurement and allows for testing well-established theories of corruption.

1: Why are traditional significance tests inadequate for analysis of big data?

2: Why do big data create new opportunities for asking and answering questions in social science?