Web Survey Bibliography
More than 50% of all survey data in the Netherlands are collected via Internet. However, these data may not adequately represent the views of the Dutch people. The majority of the Dutch people are not willing to join a web panel, and from the people that are in a panel the minority (20%) fills out the majority (80%) of the questionnaires (NOPVO, 2006). Therefore, the answers obtained from web panels can differ significantly from the general population. It is well known that panels contain too many (heavy) Internet users and too few ethnic minorities. So how can we get people into a panel that would normally not join and (hopefully) make the results more reliable? An unconventional approach is used for building this panel: via social networks. Traditionally one could make the distinction between probability and volunteer opt-in panels. Although most survey researchers agree that probability panels are needed for representativeness, the majority of web surveys is based on volunteer opt-in panels because of budget restraints. Volunteer opt-in panels are prone to selection bias, however. This new way of recruitment may increase representativeness compared to volunteer opt-in panels (recruitment is on invitation only; respondent driven sampling can be used for difficult to reach groups) while keeping the costs at a minimum. By asking respondents via friends and relatives to join the panel, respondents that are normally not willing to join a panel might be persuaded to join. The starting point of building the panel are administrative records of Breda University of Applied Sciences in the Netherlands (about 7000 students with a national spread). I will investigate response quantity, response quality, and costs and give suggestions about when to use this type of recruitment. Note that the Internet penetration rate in the Netherlands is about 90% in 2010.
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Web survey bibliography (109)
- The use of online social networks as a promotional tool for self-administered internet surveys; 2016; de Rada, V. D.; Arino, L. V. C; Blasco, M. G
- Exploring the Feasibility of Using Facebook for Surveying Special Interest Populations ; 2016; Lee, C.; Jang, S.
- Longitudinal Online Ego-centric Social Network Data Collection with EgoWeb 2.0 ; 2016; Amin, A.; Kennedy, D.
- Problems and Prospects in Survey Research; 2016; Moy, P.; Murphy, J.
- A Framework of Incorporating Thai Social Networking Data in Online Marketing Survey; 2016; Jiamthapthaksin, R.; Aung, T. H.; Ratanasawadwat, N.
- Improving social media measurement in surveys: Avoiding acquiescence bias in Facebook research; 2016; Kuru, O.; Pasek, J.
- Online and Social Media Data As an Imperfect Continuous Panel Survey; 2016; Diaz, F.; Garmon, F.; Hofman, J. K.; Kiciman, E.; Rothschild, D.
- Social Media Analyses for Social Measurement; 2016; Schober, M. F.; Pasek, J.; Guggenheim, L.; Lampe, C.; Conrad, F. G.
- Doing Surveys Online ; 2016; Toepoel, V.
- Taming Big Data: Using App Technology to Study Organizational Behavior on Social Media; 2015; Bail, C. A.
- Validation of the new scale for measuring behaviors of Facebook users: Psycho-Social Aspects of Facebook...; 2015; Bodroza, B.; Jovanovic, T.
- Facebook as a Tool for Respondent Tracing; 2015; Schneider, S. J., Burke-Garcia, A., Thomas, G.
- Predictors of inconsistent responding in web surveys; 2015; Akbulut, Y.
- Does Opinion Leadership Increase the Followers on Twitter; 2015; Hwang, Y.
- A Mixed Methods Approach to Network Data Collection; 2014; Rice, E., Holloway, I. W., Barman-Adhikari, A., Fuentes, D., Brown, C. H., Palinkas, L. A.
- Facebook, Twitter, & Qr Codes: An Exploratory Trial Examining The Feasibility Of Social Media Mechanisms...; 2014; Gu, L. L.
- Build your own social network laboratory with Social Lab: a tool for research in social media; 2014; Garaizar, P., Reips, U.-D.
- Use of a Google Map Tool Embedded in an Internet Survey Instrument: Is it a Valid and Reliable Alternative...; 2014; Dasgupta, S., Vaughan, A. S., Kramer, M. R., Sanchez, T. H., Sullivan, P. S.
- Using respondent tweets to fill in survey gaps; 2014; Murphy, J.
- The quality of ego-centered social network data in web surveys: experiments with a visual elicitation...; 2014; Marcin, B., Matzat, U., Snijders, C.
- Social Media and Surveys: Collaboration, Not Competition; 2014; Couper, M. P.
- Recent Books and Journals in Public Opinion, Survey Methods, and Survey Statistics; 2014; Callegaro, M.
- 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.
- Online Surveys as a Management Tool for Monitoring Multicultual Virtual Team Processes; 2014; Scovotti, C.
- Picking up the Bread Crumbs: Holistic Insights from Social Media; 2014; Souda, P.
- The Future of Social Media, Sociality, and Survey Research; 2013; Hill, C., Dever, J. A.
- Collecting Diary Data on Twitter; 2013; Richards, A., Dean, E., Cook, S.
- Second Life as a Survey Lab: Exploring the Randomized Response Technique in a Virtual Setting; 2013; Richards, A., Dean, E.
- Virtual Cognitive Interviewing Using Skype and Second Life; 2013; Dean, E., Head, B., Swicegood, J. E.
- Sentiment Analysis: Providing Categorical Insight into Unstructured Textual Data; 2013; Haney, C.
- Social Media, Sociality, and Survey Research; 2013; Hill, C., Dean, E., Murphy, J.
- Different approaches to measure ego-centered social support networks: a meta-analysis; 2013; Hlebec, V., Kogovsek, T.
- Online questionnaire development: Using film to engage participants and then gather attitudes towards...; 2013; Middleton, A., Bragin, E., Morley, K. I., Parker, M.
- Customer satisfaction in Web 2.0 and information technology development; 2013; Sharma, G., Baoku, L.
- Online Survey on Twitter: A Urological Experience; 2013; Dal Moro, F.
- Social media data demands a marriage of high-tech and high-touch; 2013; Waldheim, C., Stevens, N.
- Conceptualising and evaluating experiences with brands on Facebook; 2013; Smith, S.
- Discovering interest groups for marketing in virtual communities: An integrated approach; 2013; Wang, K.-Y., Wu, H.-J., Ting, I.-H.
- New social media, new social science?; 2013; Woodfield, K., Morrell, G.
- Cognitive Interviewing in Online Modes: a Comparison of Data Collected in Second Life and Skype; 2013; Swicegood, J. E., Head, B., Dean, E., Keating, M.
- Social Network Analysis and Survey Response: How Facebook Data Can Supplement Survey Data; 2013; Sage, A.
- The Use of Email, Text Messages, and Facebook to Increase Response Rates Among Adolescents in a Longitudinal...; 2013; Fleeman, A., Francis, K., Henderson, Ti., Woodford, M., Jani, M.
- Internet-Based Recruitment to a Depression Prevention Intervention: Lessons From the Mood Memos Study...; 2013; Morgan, A. J., Jorm, A. F., Mackinnon, A. J.
- Sampling online communities: using triplets as basis for a (semi-) automated hyperlink web crawler.; 2013; Veny, Y.
- Use of a Social Networking Web Site for Recruiting Canadian Youth for Medical Research; 2013; Chu, J. L., Snider, C. E.
- How and when social media storms impact brands; 2012; Morris, A., Perry, H.
- Biting the Hand and Bending the Rules: An IJMR Presentation; 2012; Pettit, A.
- A survey of social media usage integrating daily Facebook participation time with in-person social interaction...; 2012; Mishra, S.
- The integration of facebook into class management: an exploratory study; 2012; Chou, P. N.