In the Mode. . .Text-to-Web Survey Data Collection: An Exploratory Study in Preelection Polling of the U.S. Presidential Election

Abstract

As our society rapidly employs new forms of communication, new modes of data collection are challenging the best practices developed over years of polling. Preelection polling must simultaneously evolve, as new modes have emerged in the past few decades, including computer-mediated communication, mobile texting, and the use of touch tone keypads to communicate information. A tension exists between traditional and novel means of interpersonal communication, and researchers are struggling to determine which traditional methods of data collection still have a place in the modern industry. This study examined three relatively new modes of preelection poll data collection, online, mobile, and IVR (interactive voice recognition) to determine what relationships exist, if any, between the mode of data collection and the composition of a sample across eight demographic variables: age, education, gender, political affiliation, race, region, 2016 Vote History, and 2020 Vote Intention. Twenty-six preelection polls were used in the study, with each poll ranging in collection dates between August 30 and October 31, 2020. The total combined sample size for this study is n = 19,886; 49% were IVR respondents ( n = 9,795), 25% was collected from online panels ( n = 5,039), and 25% was collected from short message service (SMS)-to-web respondents ( n = 5,052). A χ2 (chi-square) test for association was conducted using a significance level of p < .05 and a 95% confidence interval (CI) and found a significant difference between each mode of data collection across the eight aforementioned variables. A significant difference between political party affiliation/registration and mode of data collection was attributed to the educational attainment of individuals participating in each preelection polls based on the mode of data collection. This study suggests that underlying variables within the sample composition of different modes of data collection can have an impact on the accuracy of preelection polls.