Web Survey Bibliography
User modeling is traditionally applied to systems were users have a large degree of control over their goals, the content they view, and the manner in which they navigate through the system. These systems aim to both recommend useful goals to users and to assist them in achieving perceived goals. Systems such as online or telephone surveys are different in that users have only a singular goal of survey completion, extremely limited control over navigation, and content is restricted to prescribed set of survey tasks; changing the user modeling problem to one in which the best means of assisting users is to identify rare-actions hazardous to their singular goal, by observing their interactions with common contexts. With this goal in mind, predictive mechanisms based on a combination of Machine Learning classifiers and survey domain knowledge encapsulated in sets of rules are developed that utilize user behavioral, demographic, and survey state data in order to predict when user actions leading to irreparable harm to the user's singular goal of successful survey completion will occur. We show that despite a large class imbalance problem associated with detecting these actions and their associated users, we are able to predict such actions at a rate better than random guessing and that the application of domain knowledge via rule-sets improves performance further. We also identify traits of surveys and users that are associated with rare-action incidence. For future work, it is recommended that existence of potential sub-concepts related to users who perform these rare-actions be explored, as well as exploring alternative means of identifying such users, and that system adaptations be developed that can prevent users from performing these rare and harmful actions.
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Web survey bibliography - Thesis, diplomas (29)
- A Meta-Analysis of the Effects of Incentives on Response Rate in Online Survey Studies; 2017; Mohammad Asire, A.
- Designing web surveys for the multi-device internet; 2015; de Bruijne, M.
- Rating Scales in Web Surveys: A Test of New Drag-and-Drop Rating Procedures; 2015; Kunz, T.
- Mixed-method feasibility study comparing the outpatient assessment of burn patients using a tablet device...; 2015; Mitchell, S. S.
- Facebook, Twitter, & Qr Codes: An Exploratory Trial Examining The Feasibility Of Social Media Mechanisms...; 2014; Gu, L. L.
- Open-ended questions in Web Surveys-Using visual and adaptive questionnaire design to improve narrative...; 2014; Emde, M.
- Design and Implementation of an Online Questionnaire Tool; 2014; Schaniel, R.
- User Modeling via Machine Learning and Rule-Based Reasoning to Understand and Predict Errors in Survey...; 2013; Stuart, L. C.
- Investigation of background acoustical effect on online surveys: A case study of a farmers' market...; 2013; Tang, Xi.
- Developing a New Mixed-Mode Methodology For a Provincial Park Camper Survey in British Columbia; 2013; Dyck, B. W.
- Classifying Mouse Movements and Providing Help in Web Surveys; 2013; Horwitz, R.
- Satisficing in Web Surveys: Implications for Data Quality and Strategies for Reduction; 2013; Zhang, Che.
- “I think I know what you did last summer” Improving data quality in panel surveys; 2012; Lugtig, P. J.
- Analyzing Functionalities for Online Questionnaire System (OQS); 2012; Atown, H. Y.
- Web panels in Slovenia; 2011; Lenar, J.
- Clarifying Survey Questions; 2011; Redline, C. D.
- Nonresponse and Measurement Error in Mobile Phone Surveys ; 2010; Kennedy, C.
- Internet-Based Measurement With Visual Analogue Scales: An Experimental Investigation; 2010; Funke, F.
- Social Networking Sites: Evaluating and Investigating their use in Academic Research; 2010; Redmond, F.
- E-epidemiology : Adapting epidemiological methods for the 21st century; 2009; Bexelius, C.
- Visual Design Effects on Respondents’ Behavior in Web-Surveys; 2009; Greinoecker, A.
- Improving survey response in mail and internet general public surveys using address-based sampling and...; 2009; Messer, B. L.
- Design Variations in Adaptive Web Sampling; 2008; Vincent, K. S.
- Internet-based survey design for university web sites : a case study of a Thai university ; 2007; Vate-U-Lan, P.
- On the cost-efficiency of probability sampling based mail surveys with a Web response option; 2005; Werner, P.
- Cognitive Laboratory Experiences : On Pre-testing Computerised Questionnaires; 2002; Snijkers, G.
- (Non)Response bei Web-Befragungen; 2002; Bosnjak, M.
- Web survey errors; 2001; Lozar Manfreda, K.
- A study of factors affecting responses in electronic mail surveys; 1997; Good, K. P.