Data in the Social Sciences

SOST10042 Data in the Social Sciences 20 Semester 2 Undergraduate Level 1 Alexandru Cernat Unit coordinator Social Statistics 1 FHEQ level (Framework for Higher Education Qualifications) ' First part HE study/Bachelors ' European Credit Transfer & Accumulation System Rating : 10.0 This unit introduces students to the landscape of data in the social sciences, from traditional survey data to new and emerging sources such as digital trace data, social media content, and biological and administrative measures. The course begins by examining how conventional data sources—particularly surveys—are collected and evaluated using established frameworks for data quality. These frameworks are then applied to assess newer types of data that are increasingly used in social research. In doing so, students will learn to critically evaluate how different data sources are generated and what assumptions and limitations they have. The unit also provides foundational skills for accessing and working with different data types, helping students understand how data quality affects the conclusions we can draw from social research.  This unit introduces students to the landscape of data in the social sciences, from traditional survey data to new and emerging sources such as digital trace data, social media content, and biological and administrative measures. The course begins by examining how conventional data sources—particularly surveys—are collected and evaluated using established frameworks for data quality. These frameworks are then applied to assess newer types of data that are increasingly used in social research. In doing so, students will learn to critically evaluate how different data sources are generated and what assumptions and limitations they have. The unit also provides foundational skills for accessing and working with different data types, helping students understand how data quality affects the conclusions we can draw from social research.  The unit aims to:- Introduce students to the different types of data used in the social sciences, including both traditional and emerging data sources.- Explore the processes through which data are generated, focusing initially on survey research before extending to new forms of data such as digital trace data, social media data, and biological data.- Provide students with conceptual frameworks for understanding and evaluating data quality.- Develop students’ ability to critically assess how different data sources are created, their strengths and limitations, and their suitability for answering social science questions.- Equip students with basic skills to access, work with, and assess the quality of diverse social data sources.    Students should be able to:Describe key types of data in the social sciences (e.g., survey, digital, biological, administrative). Explain how different data sources are generated and how this affects data quality.  Apply basic frameworks for evaluating data quality.   Students should be able to:Compare strengths and limitations of different data sources.  Analyse how the data generating process influences bias and measurement. Reflect on consent and privacy issues in using different types of data.  Students should be able to:Access and explore different types of data using statistical software. Assess the quality of data using different conceptual frameworks. Students should be able to:Communicate findings clearly using text, tables, and visualisations. Be aware of ethical and privacy considerations when sourcing and using data.    Syllabus (indicative curriculum content):Introduction: The Role of Data in the Social Sciences  - What is data? Why does it matter?  - Overview of traditional and emerging data sources.The Data Generating Process  - Concepts of measurement, observation, and inference in the social sciencesSurvey Data: Collection and Quality Frameworks  - Modes of data collection (face-to-face, telephone, online)  - Sampling, nonresponse, and measurement error  - Introduction to data quality frameworks (e.g. Total Survey Error)New Forms of Data in the Social Sciences  - Digital trace data (web scraping, sensor data, app logs, URLs)  - Social media data (Twitter, Facebook, Reddit, etc.)  - Biological and administrative data (biomarkers, register-based data)Applying Data Quality Concepts to New Data  - Coverage, selection bias, missingness, measurement issues  - Comparability with traditional sources  - Ethical and legal considerations (e.g. consent, privacy)Working with Different Types of Data  - Accessing and exploring public datasets (e.g.   Understanding Society, UK Biobank, social media APIs)  - Hands-on practical sessions using statistical softwareCase Studies in Social Data Use  - Comparative analysis using traditional and new data  - Evaluating published studies for data quality and validity  - Examples from public health, political behaviour, online platformsSummary and Reflection  - Key takeaways about data generation and use  - Responsible and critical data use in social research   The course will be a combination of lectures and hands-on seminars and computer labs. Lectures will be used to convey key concepts and show real world applications using social data. The hands-on computer labs will help students learn how to work with different types of data and understand their strengths and weaknesses.  0 Other 100% Survey Design Critique and Analysis (using different data) - 1,000 words (40%)Hands on evaluation of social data quality (using different data) - 1,500 words (60%) Online feedback within 15 working days. BA(Hons) Econ & Soc Std BAEcon (DS & Econ) First Year Mandatory Y Groves, R.M., Fowler, F.J. Jr., Couper, M.P., Lepkowski, J.M., Singer, E., and Tourangeau, R. (2009). Survey Methodology, 2nd Edition. New York: Wiley.Keusch, F., Struminskaya, B., Eckman, S., & Guyer, H. (in preparation). Data collection with wearables, apps, and sensors. Chapman and Hall/CRC.  https://bookdown.org/wasbook_feedback/wasO'Toole, T., Cernat, A., Tzavidis, N., Shlomo, N., & Sakshaug, J. (2025, May). Survey Practice Guide 1: Data integration – Options for integrating survey and non-survey data. Survey Futures Practitioner Guides: https://surveyfutures.net/wp-content/uploads/2025/05/survey-practice-guide-1-data-integration.pdf   Lectures 10 Seminars 10 180