Entertainment, Intelligent, or Hybrid Programming? An Automated Content Analysis of 12 Years of Political Satire Interviews

ABSTRACT

The research considers the balance of intellectual versus entertainment-oriented individuals appearing as interview guests on political satire programs. Specifically, the analysis employs semi-supervised learning to categorize the occupations of individuals appearing on The Daily Show and The Colbert Report between 2003 and 2014 (N = 3,507). The results confirm that satire programs have become an important outlet for politicians and journalists looking to connect with a younger audience. More often than not, these guest appearances privilege a newsworthy and intellectually oriented discussion of contemporary issues and ideas as opposed to the promotion of entertainment content. Important to note, the data set represents the largest body of political satire content analyzed to date and the results confirm the value of applying automated and semi-supervised learning coding within communication research. We conclude by discussing the methodological contributions of our coding process, future directions for political comedy research, and the scalable potential of automated coding efforts.

Acknowledgment

This research was presented at the 2015 annual conference of the International Communication Association.

Notes

¹ We assumed 100% accuracy for our manual coding process, given that we checked each individual against their DBpedia entry and related information from Wikipedia and the Comedy Central website. Further, as noted in the article, the second author also confirmed the accuracy of the manual effort by reviewing a subset (~10%) of the coded entries. Lindbergh (2016b) made the same assumption about reliability and accuracy in his analysis of the guests appearing during the first 100 days of Colbert’s The Late Show.