Data Science and "Big Data" in
Communication Research

Michael W. Kearney
Department of Communication Studies
Center for Research Methods & Data Analysis
University of Kansas

Some background

Research interests


New data sources



*quick note about organization


There is no evidence that 3-5 million illegal votes were cast in the 2016 U.S. election.


Quantitative communication research is not perfect.

Issues in COMS research

"Replication crisis"

1. p-hacking


2. Open data


Technological advances present new challenges to communication researchers.

New challenges


Technological advances present new opportunities to communication researchers.

Big data

Dealing with big data

Data science

Quantitative research


Data science



Communication researchers should leverage data science tools and methods.

Better samples


Better samples


Bigger questions


Research questions


User networks



Network analysis





Communication researchers have an obligation to use data science.

Big data baggage

Two approaches

Computer science examines whether a certain pattern can be found in data.

Statistics examines whether data can be found in a certain pattern.

Two approaches

Competing models

Machine learning problems

Theory hangs in the balance

Communication studies


That's it \o/



Vasant, D. (2013). Data science and prediction. Communications of the ACM, 56, 64-73.

Provost, F., & Fawcett, T. (2013). Data science and its relationship to big data and data-driven decision making. Big Data, 1, 51-59.