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Real-time response (RTR) measurement is an important technique for analyzing human processing of electronic media stimuli. Although it has been demonstrated that RTR data are reliable and internally valid, some argue that they lack external validity. The reason for this is that RTR measurement is restricted to a laboratory environment due to its technical requirements. This paper introduces a smartphone app that 1) captures real-time responses using the dial technique and 2) provides a solution for one of the most important problems in RTR measurement, the (automatic) synchronization of RTR data. In addition, it explores the reliability and validity of mobile RTR measurement by comparing the real-time reactions of two samples of young and welleducated voters to the 2013 German televised debate. Whereas the first sample participated in a classical laboratory study, the second sample was equipped with our mobile RTR system and watched the debate at home. Results indicate that the mobile RTR system yields similar results to the lab-based RTR measurement, providing evidence that laboratory studies using RTR are externally valid. In particular, the argument that the artificial reception situation creates artificial results has to be questioned. In addition, we conclude that RTR measurement outside the lab is possible. Hence, mobile RTR opens the door for large-scale studies to better understand the processing and impact of electronic media content. [ABSTRACT FROM AUTHOR]

Recent years have seen an increase in the amount of statistics describing different phenomena based on "Big Data." This term includes data characterized not only by their large volume, but also by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, and the way in which they are collected and disseminated is fundamental. This change constitutes a paradigm shift for survey research. There is great potential in Big Data, but there are some fundamental challenges that have to be resolved before its full potential can be realized. This report provides examples of different types of Big Data and their potential for survey research; it also describes the Big Data process, discusses its main challenges, and considers solutions and research needs. [ABSTRACT FROM AUTHOR]