Course content
Session 1: Introduction to the course, and Digital ethnographic field studies
In the Introduction part, we will go through an overview of digital research methodologies and criteria for comparing their strengths and weaknesses when it comes to find answers to students' research questions.
In the digital ethnographic field studies part, the emphasis will be on immersive, participatory and reflexive modes of research. Themes include: constituting the field, moving between online and offline settings, the uses of found (big) data versus gathering primary data, corpora, repositories and memos. We will also discuss the iterative research process and concurrent data gathering and analyses. Exemplary digital software will be introduced. Students will learn to critically evaluate when to employ a method based on considerations of research needs, resource availability, and ethical considerations.
Compulsory reading. Reading list will be provided by the start of the academic year.
Session 2: Online Community Research: Research on “networked public spheres”
Online communities are particularly fruitful research contexts as they allow insight into naturally occurring large-scale online conversations surrounding a wide range of topics. Collecting, structuring, and analyzing such conversations allows researchers, among others, to understand which topics are being discussed, how they develop over time, which actors are driving a conversation, which viewpoints are (un)popular or controversial in a community and which sentiment a specific conversation or response may elicit. During this session, we will discuss how to collect as well as meaningfully structure and analyze large-scale conversation data in comparison to small-scale interview data. Furthermore, we will weigh potential implications and ethical boundaries of those methods.
Compulsory reading. Reading list will be provided by the start of the academic year.
Session 3: Social Network Analysis: Exploring the Web of Connections
Social networks form the backbone of modern society, influencing everything from individual opportunities to global trends. Understanding the structure and dynamics of these networks allows us researchers to answer critical questions about relationships, influence, and behavior. In this session, we will explore the fundamentals of social networks, their significance in contemporary research, and the insights they offer. We will discuss methods for collecting social network data, examine common sources, and address challenges such as data quality and access. Through practical exercises, we will learn how to analyze network data to uncover key patterns, relationships, and structures. Finally, we will interpret the results of network analysis and consider the broader implications, including ethical considerations.
Compulsory reading. Reading list will be provided by the start of the academic year.
Session 4: Computational communication research: Machine learning for automated content analysis
Text and image analysis are fundamental to understanding media framing, agenda-setting, and persuasion. While traditional content analysis requires substantial human resources, computational approaches have revolutionized how we process and analyze communication data. This session explores three major computational approaches: dictionary-based methods, machine learning, and Large Language Models (LLMs).
The session begins with an overview of traditional dictionary-based approaches and machine learning classification techniques for automated content analysis. We then focus extensively on the transformative potential and limitations of generative LLMs in communication research. Students will learn to critically evaluate when to employ each method based on research needs, resource availability, and ethical considerations.
Compulsory reading for session 4: Reading list will be provided before the start of the course.
Session 5: Digitalizing experiments – from online games to virtual reality
In the increasing digitalized world people interact with devices and AI for most of their daily tasks. The study of communication behavior is shifting towards digital environments, capturing human-machine interactions, and integrating the use of wearables. This also allows for interesting opportunities to integrate digital tools into experimental designs and methods. Researchers have done so in various ways, by using virtual reality for interventions and measurement of biases, by using eye tracking, or by immersing the participant even more into the digital setting and integrated AI solutions and chatbots to measure outcomes. We will discuss the methods and techniques, as well as the potential implications and ethical boundaries of those methods.
Compulsory reading. Reading list will be provided by the start of the academic year.
Session 6: Summing up and presenting choice of research methods
In the first part, we discuss students' considerations of the best digital research method to answer their research question posed on session 1. The second part is a round-table session. Students present their methodological choice to supervisors and course professors and get feedback.
There is no compulsory reading for this session.