Consolidating Communication Research Through Causal Inference

About the Workshop

The societal impact of communication motivated the establishment of communication studies. However, establishing causality within the field remains challenging, especially in technologically mediated contexts. Communication is a diverse field, and causal interpretations vary across traditions. This workshop will explore how different subfields address causality, emphasizing the need for causal explanations to enhance theory building. It will also discuss methodological approaches, challenges, and future directions for establishing causality in communication research.

Session Goals

Communication scholars are keen on understanding the cause and effects of various communication phenomena in both interpersonal and mediated contexts, and many communication theories are in fact causal. While the question of causality is not new, it has recently attracted more attention because of the unprecedented prevalence of digital trace data, which along with the availability of various publicly accessible datasets, provide unique opportunities for communication scholars to ask innovative research questions with causal inference based on observational data, yielding greater ecological validity. However, institutions have yet to incorporate these methodological advancement in their curricula. This workshop will introduce and discuss modern causal inference methods, more common in other social sciences, that can be used to determine a true cause-and-effect relationship in both quantitative and qualitative communication science. Specifically, we will focus on how communication researchers could harness causal inference thinking, designs and methods to advance their inquiries into communication phenomena.

Outcomes

We are a very dispersed discipline and even the definition of what is “causal” differs by communication subfield. Therefore, the goal is to learn how the different subfields of communication engage with the issue and learn from each other. We hope that the workshop will lead to a discussion about a possible special issue and a development of a more organized group of researchers interested in causality in communication science.

Organizers

Shuning Lu

Philip Merrill College of Journalism, University of Maryland, College Park

Ewa Maslowska

Institute of Communications Research, University of Illinois Urbana-Champaign

Harsh Taneja

Institute of Communications Research, University of Illinois Urbana-Champaign

Nathan Walter

School of Communication, Northwestern University

Speakers

Helena Bilandzic

Department of Media, Knowledge, and Communication, University of Augsburg

Pascal Jürgens

Trier University

Sebastian Valenzuela

School of Communications, Pontificia Universidad Católica de Chile

Tian Yang

School of Journalism and Communication, The Chinese University of Hong Kong

Guiding questions

1. How, if at all, can we use causal inference to develop new theories and sunset older ones?
2. Should we consider ‘relaxing’ key requirements of causal inference when studying and theorizing about communication in the real-world?
3. What kind of data is needed to make causal inferences across levels of analysis (e.g., individuals, teams, communities, societies)?
4. What is the role of causal inference in qualitatively-driven inquiry and community-based participatory research?

Resources