SJMC Team Wins Top Paper Award

SJMC Team Wins Top Paper Award Studying “The Temporal Turn in Communication Research”

School of Journalism and Mass Communication (SJMC) faculty and students won a top paper award from the Computational Methods Interest Group of the International Communication Association (ICA) for their paper, “The Temporal Turn in Communication Research.” The award will be presented at the 69th ICA Conference in Washington, D.C. on May 26, 2019.

Led by Chris Wells of Boston University, the authors of the award-winning paper include SJMC faculty Dhavan Shah, current and former SJMC graduate students Jordan Foley, Josephine Lukito, Ayellet Pelled and JungHwan Yang, and UW political science professor Jon Pevehouse.

Time series analysis has been around for quite some time, however, the SJMC team’s innovation comes from how they use “big data” to apply the method to the modern communication ecology.

“Our paper is looking at the field emerging when these come together: how we can use time series on computational data to better understand our media system,” Chris Wells said.

Wells further elaborated on how the paper uses early research to determine future developmental directions, as well as areas of challenge and caution for future researchers. As the first review and synthesis of this new approach, the University of Wisconsin-Madison’s Mass Communication Research Center and its Civic Culture and Contentious Politics and Social Media and Democracy research groups are bringing innovation to a new level.

“We already have been using many of the techniques we describe, and we noticed some other scholars were also using them,” Wells said. “But we also noticed that we and these few other scholars were doing a lot of innovating – there were not a lot of established ground rules, or best practices, for this kind of research.”

Similarly, Josephine Lukito believes the paper embodies a core theme of innovation due to how it demonstrates how conversations change over time.

“As social scientists, we know that language is dynamic – conversations have an ebb and flow, and topics become more or less popular over time,” Lukito said. “But we usually study this stuff cross-sectionally, like a frozen snapshot. Time series methods allow us to move beyond that, to look at political discourse as it develops.”

Jordan Foley notes the paper synthesizes theoretical and methodological conversations in the discipline. Furthermore, Foley discusses the presence of a gap lying between theoretical discussion and the operationalized power of time series analysis.

“It speaks to (1) the emergence of computational research techniques and (2) new sources of fine-grained, temporally structured data,” Foley said. “In the paper, we refer to the intersection of these developments as computational communication science using time series analysis.”