Web Survey Bibliography
Public opinion research is entering a new era, one in which traditional survey research may play a less dominant role. The proliferation of new technologies, such as mobile devices and social media platforms, are changing the societal landscape across which public opinion researchers operate. The ways in which people both access and share information about opinions, attitudes, and behaviors have gone through perhaps a greater transformation in the last decade than in any previous point in history and this trend appears likely to continue. The rapid adoption of smartphones and ubiquity of social media are interconnected trends which may provide researchers with new data collection tools and alternative sources of information to augment or, in some cases, provide alternatives to more traditional data collection methods. However, this brave new world is not without its share of issues and pitfalls – technological, statistical, methodological, and ethical. As the leading association of public opinion research professionals, AAPOR is uniquely situated to examine and assess the potential impact of these “emerging technologies” on the broader discipline and industry of opinion research. In September 2012, AAPOR Council approved the formation of the Emerging Technologies Task Force with the goal of focusing on two critical areas: smartphones as data collection vehicles and social media as platform and information source. The purposes of the task force are to: ● define and delineate the scope and landscape of each area; ● describe the potential impact in terms of quality, efficiency, timeliness and analytic reach; ● discuss opportunities and challenges based on available research; ● delineate some of the key legal and ethical considerations; and ● detail the gaps in our understanding and propose avenues of future research. The report here examines the potential impact of mobile technologies on public opinion research – as a vehicle for facilitating some aspect of the survey research process (i.e., recruitment, questionnaire administration, reducing burden, etc.) and/or augmenting or replacing traditional survey research methods (i.e., location data, visual data, and the like).
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Reports, seminars
Web survey bibliography (4086)
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Switching the polarity of answer options within the questionnaire and using various numbering schemes...; 2014; Struminskaya, B., Schaurer, I., Bosnjak, M.
- Measuring the very long, fuzzy tail in the occupational distribution in web-surveys; 2014; Tijdens, K. G.
- Social Media and Surveys: Collaboration, Not Competition; 2014; Couper, M. P.
- Improving cheater detection in web-based randomized response using client-side paradata; 2014; Dombrowski, K., Becker, C.
- Interest Bias – An Extreme Form of Self-Selection?; 2014; Cape, P. J., Reichert, K.
- Online Qualitative Research – Personality Matters ; 2014; Tress, F., Doessel, C.
- Increasing data quality in online surveys 4.1; 2014; Hoeckel, H.
- Moving answers with the GyroScale: Using the mobile device’s gyroscope for market research purposes...; 2014; Luetters, H., Kraus, M., Westphal, D.
- The effectiveness of recruitment strategies on general practitioner's survey response rates - a...; 2014; Pit, S. W., Pyakurel, S., Vo, T.
- Respondent-Driven Sampling of Heterosexuals at Increased Risk of HIV Infection; 2014; Batra, P., Gray, S. C., Krishna, N., Prachand, N., Robinson, W. T., Wejnert, C.
- Two Are Better Than One: The Use of a Mixed-Mode Data Collection to Improve the Electoral Forecast; 2014; de Rada, V. D., Pasadas del Amo, S.
- Social desirability is the same in offline, online, and paper surveys: A meta-analysis; 2014; Dodou, D., de Winter J. C. F.
- The impact of contact effort on mode-specific selection and measurement bias; 2014; Schouten, B., van der Laan, J., Cobben, F.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- User-Generated Online Health Content: A Survey of Internet Users in the United Kingdom; 2014; Ziebland, S., Valderas, J., Lupianiez-Villanueva, F., O'Neill, B.
- Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information...; 2014; Schweiger, S., Oeberst, A., Cress, U.
- Social Media and Online Survey: Tools for Knowledge Management in Health Research ; 2014; Merolli, M., Sanchez, F. J. M., Gray, K.
- Using Online Social Media for Recruitment of Human Immunodeficiency Virus-Positive Participants: A Cross...; 2014; Yuan, P., Bare, M. G., Johnson, M. O., Saberi, P.
- Mobile Technologies for Conducting, Augmenting and Potentially Replacing Surveys: Report of the AAPOR...; 2014; Link, M. W., Murphy, J., Schober, M. F., Buskirk, T. D., Childs, J. H., Tesfaye, C.
- Undisclosed Privacy: The Effect of Privacy Rights Design on Response Rates; 2014; Haer, R., Meidert, N.
- Modelling ”don’t know” responses in rating scales; 2014; Manisera, M., Zuccolotto, P.
- Do Incentives Commoditize Surveys Or Reinforce The Relationship Economy?; 2014; Murphy, L.
- Does Gamification Work? - A Literature Review of Empirical Studies on Gamification ; 2014; Hamari, J., Koivisto, J., Sarsa, H.
- Clicking vs. Dragging: Different Uses of the Mouse and Their Implications for Online Surveys; 2014; Sikkel, D., Steenbergen, R., Gras, S.
- The Effect of Benefit Wording on Consent to Link Survey and Administrative Records in a Web Survey; 2014; Sakshaug, J. W., Kreuter, F.
- Completion rates and non-response error in online surveys: Comparing sweepstakes and pre-paid cash incentives...; 2014; LaRose, R., Tsai, H. S.
- The accuracy of self-reported medical history: A preliminary analysis of the promise of internet-based...; 2014; Kelstrup, A. M., Juillerat, P., Korzenik, J.
- Panel Attrition - Separating Stayers, Fast Attriters, Gradual Attriters, and Lurkers; 2014; Lugtig, P. J.
- Dropout Rates and Response Times of an Occupation Search Tree in a Web Survey; 2014; Tijdens, K. G.
- The use of within-subject experiments for estimating measurement effects in mixed-mode surveys ; 2014; Klausch, L. T., Schouten, B., Hox, J.
- Is it what you say, or how you say It? An experimental analysis of the effects of invitation wording...; 2014; Fazekas, Z., Wall, M. T., Krouwel, A.
- Improving the Representativeness of Online Surveys ; 2014; Henning, J.
- GESIS Panel: Sample and Recruitment; 2014
- Online Surveys as a Management Tool for Monitoring Multicultual Virtual Team Processes; 2014; Scovotti, C.
- How much is shorter CAWI questionnaire VS CATI questionnaire?; 2014; Bartoli, B.
- WEBDATANET: A Network on Web-based Data Collection, Methodological Challenges, Solutions, and Implementation...; 2014; Tijdens, K. G., Steinmetz, S., de Pedraza, P., Serrano, F.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- Incentives on demand in a probability-based online panel: redemption and the choice between pay-out...; 2014; Schaurer, I., Struminskaya, B., Kaczmirek, L.
- The Effect of De-Contextualisation - A Comparison of Response Behaviour in Self-Administered Surveys; 2014; Wetzelhuetter, D.
- Responsive designed web surveys; 2014; Dreyer, M., Reich, M., Schwarzkopf, K.
- Extra incentives for extra efforts – impact of incentives for burdensome tasks within an incentivized...; 2014; Schreier, J. H., Biethahn, N., Drewes, F.
- Students First Choice – the influence of mobile mode on results; 2014; Maxl, E.
- Device Effects: How different screen sizes affect answer quality in online questionnaires; 2014; Fischer, B., Bernet, F.
- Moving towards mobile ready web panels; 2014; Wijnant, A., de Bruijne, M.
- Innovation for television research - online surveys via HbbTV. A new technology with fantastic opportunities...; 2014; Herche, J., Adler, M.
- Mixed-devices in a probability based panel survey. Effects on survey measurement error; 2014; Toepoel, V., Lugtig, P. J.
- Online mobile surveys in Italy: coverage and other methodological challenges; 2014; Poggio, T.
- Distress Tolerance as a Predictor of Risky and Aggressive Driving; 2014; Beck, K. H., Ali, B., Daughters, S. B.
- African-American breast cancer survivors’ preferences for various types of physical activity interventions...; 2014; Paxton, R., Nayak, P., Taylor, W., Chang, S., Courneya, K., Schover, L., Hodges, K., Jones, L.