Public Opinion Quarterly Special Issue Call for Papers: New Data in Social and Behavioral Research Deadline: February 1, 2020
Guest editors Frederick G. Conrad, University of Michigan, Editor Florian Keusch, University of Mannheim, Associate Editor Michael F. Schober, The New School, Associate Editor
Public Opinion Quarterly seeks submissions for a special issue of the journal devoted to new types of data that might be used to conduct social or behavioral research either in conjunction with surveys, in place of surveys, or to address questions that cannot be addressed by surveys.
Examples of these new data include social media posts, search strings, online prices, and sensor data such as location, activity, and sound. As such examples illustrate, these new data potentially can be used in social or behavioral research after having been repurposed, e.g., when researchers analyze search strings as a window onto public opinion even though the users who created these strings did so for entirely different reasons. Other times, these data are collected directly for their intended purpose (Taylor 2013), e.g., when smartphone owners are recruited into a study so that researchers may capture their mobility using the sensors built into their devices.
Regardless of the origin of these new data, they are markedly different from survey data. In stark contrast to survey responses that are produced by asking carefully crafted questions, these new data are not elicited by the researchers who later analyze them. In contrast to designed survey data, the structure of these new data is often not known ahead of time. Instead, these data are “organic” (Groves 2011), i.e., continuously generated byproducts of everyday processes. And, compared to survey data sets, these new data are massive and generally far less expensive to create.
Much has been written and spoken about the promise of these new data for conducting social and behavioral research (e.g., the AAPOR Big Data task-force report; Japec et al. 2015). The contributions published in the special issue will help assess how well this promise has been realized so far and will help sharpen predictions of future success using these alternative data.
Potential topics for submissions include, but are certainly not limited to:
* The integration of social media content with survey data * The use of call records and other mobile network operating data to study behavior * Analysis of administrative records to reduce survey costs and burden on respondents * Issues of ethics and privacy when using these new data * Measurement error in new data sources * The feasibility of tracking public opinion via Internet search terms and browsing behavior * Comparison of estimates from self-reports and data collected passively with sensors
Submissions can be methodological in orientation or can be substantive applications that demonstrate the usefulness and assess the validity of these new data sources.
The issue is scheduled for publication in early 2021. Submissions of relevant research articles, research syntheses, and research notes are welcome and will be considered through February 1, 2020.
Manuscripts should be uploaded at http://mc.manuscriptcentral.com/poq, following the manuscript preparation instructions provided on the journal’s website. To ensure consideration in the special issue, authors must include a cover letter that clearly states that the manuscript has been submitted for consideration for the 2021 “New Data special issue.” Submissions will be peer-reviewed in accord with standard journal practice. Queries about this special issue should be directed to Frederick Conrad (fconrad@umich.edu) using the subject line “2021 New Data Special Issue.”
References Groves, Robert M. 2011. “Three Eras of Survey Research.” Public Opinion Quarterly 75:861-71. Japec, Lilli, Frauke Kreuter, Marcus Berg, Paul Biemer, Paul Decker, Cliff Lampe, Julia Lane, Cathy O’Neil, and Abe Usher. 2015. “Big Data in Survey Research: AAPOR Task Force Report.” Public Opinion Quarterly 79:839-80. Taylor, Sean J. 2013. “Real Scientists Make Their Own Data.” Available at http://seanjtaylor.com/post/41463778912/real-scientists-make-their-own-data.