Web Survey Bibliography
Large amounts and varieties of data have gained the interest of various industrial companies as well as fed the ever expanding need of the public for information exchange. At the same time, internet sites that are evaluated by target audiences have increased in number, so the public can visit the targeted web sites and evaluate them based upon their firsthand opinions. Since the public rather than experts are making these assessments, there will inevitably be evaluators with views contrary to other evaluators. In order to use the information from such preference assessments of web sites effectively, it is important to consider the accuracy of the estimation of this public opinion observed through web-based surveys. Therefore, we capture the latent features of the information, categorize subjects based on their preferences, and identify the obtained latent features to the categorized clusters. We propose a method to capture this latent structure of the evaluation data as fuzzy clusters, and through the fuzzy clusters to identify the features of the various categorized subjects. In addition, using the same scales of degree of belongingness of subjects to fuzzy clusters, temporal difference over the different industries are captured through the similarity of fuzzy clusters. We show a better performance by using numerical examples.
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Web survey bibliography (4086)
- Approaches to empiric ablation of slow pathway: results from the Canadian EP web survey; 2012; Laish-Farkash, A., Shurrab, M., Tiong, I., Verma, A., Amit, G., Kiss, A., Morriello, F., Singh, S.,...
- Statistical Disclosure Control; 2012; Hundepool, A., Domingo-Ferrer, J., Franconi, L., Giessing, S., Schulte Nordholt, E., Spicer, K., de...
- Methodology of the RAND Continuous 2012 Presidential Election Poll ; 2012; Kapteyn, A., Meijer, E., Weerman, B.
- How and when social media storms impact brands; 2012; Morris, A., Perry, H.
- (Online) Access Panels: Types and Quality Standards; 2012; Bosnjak, M.
- Biting the Hand and Bending the Rules: An IJMR Presentation; 2012; Pettit, A.
- Passive measurement of online data in Practice - A White Paper Wakoopa; 2012
- Using response probabilities for assessing representativity; 2012; Bethlehem, J.
- Analysis of Web Survey Data based on Similarity of Fuzzy Clusters; 2012; Chiba, R., Sato-Ilic, M.
- Disentangling Mode-Specific Selection and Measurement Bias in Social Surveys; 2012; Buelens, B., van der Laan, J., Schouten, B., Klausch, L. T., van der Brakel, J., Burger, J.
- The efficiency and effectiveness of mixed mode versus single mode designs; 2012; Blunsdon, B.
- The National Survey of College Graduates: Developing a Web Data Collection Component; 2012; Thornton, T.
- Automated Web Testing Using Selenium; 2012; Gaston, D., Fanning, S., Daher, L.
- Mixed Mode: Phone and Web Discussion on Efficient Strategies; 2012; Gagnon, M.
- The Measurement of Consistency in Online Research; 2012; Gittelman, S. H., Trimarchi, E.
- Thinking Differently About How to Select Respondents for Surveys; 2012; Terhanian, G., Bremer, J.
- Benefits of Modular Design for Mobile and Online Surveys; 2012; Kelly, F., Johnson, A., Stevens, S.
- Emerging Techniques of Respondent Engagement: Leveraging Game and Social Mechanics for Mobile Application...; 2012; Lai, J. W., Vanno, L.
- An Introduction to Using Video for Research; 2012; Jewitt, C.
- A Machine Learning Based Topic Exploration and Categorization on Surveys; 2012
- Survey Swipe; 2012; Macer, T.
- A Framework for the Collection of Universal Client Side Paradata (UCSP); 2012; Kaczmirek, L.
- Improving ability measurement in surveys by following the principles of IRT: The Wordsum vocabulary...; 2012; Cor, K., Haertel, E., Krosnick, J. A., Malhotra, N.
- Online Surveys Aren't Just for Computers Anymore! Exploring Potential Mode Effects between Smartphone...; 2012; Buskirk, T. D., Andrus, C.
- Why do survey participants choose to report by Web, paper, or not at all? Results from an American Community...; 2012; Nichols, E. M.
- Worldwide online research spending; 2012
- Using paradata to explore item-level response times in surveys; 2012; Couper, M. P., Kreuter, F.
- Using multivariate statistics, 6th Edition; 2012; Tabachnick, B. G., Fidell, L. S.
- Unintentional mobile respondents; 2012; Peterson, G.
- Tracking preference expression (DNT); 2012
- The smartphone psychology manifesto; 2012; Miller, G.
- The practice of social research; 2012; Babbie, E. R.
- The integration of facebook into class management: an exploratory study; 2012; Chou, P. N.
- The effects of item saliency and question design on measurement error in a self-administered survey; 2012; Stern, M. J., D., Mendez, J. D.Smyth, J. D.
- The cross platform report. Q2 -2012 - US; 2012
- Smartphone ownership update: September 2012; 2012; Rainie, L.
- Selection bias of internet panel surveys: A comparison with a paper-based survey and national governmental...; 2012; Tsuboi, S., Yoshida, H., Ae, R., Kojo, T., Nakamura, Y., Kitamura, K.
- Screenwise panel: Frequently Asked Questions; 2012
- Research company spotlight - Mobile surveys; 2012
- Quality in market research. From theory to practice. 2nd Edition; 2012; Harding, D., Jackson, P.
- Participation of mobile users in traditional online studies; 2012; Jue, A.
- Online survey statistics for the mobile future. Updated with Q3 2012 data; 2012
- Ofcom technology tracker Wave 2; 2012
- Not just playing around; 2012; Ewing, T.
- Norme di qualita' Assirm (Assirm quality rules]; 2012
- NBCU enlists Google, ComScore to track multiscreen Olympics viewing; 2012; Spangler, T.
- MRS Guidelines for online reseach; 2012
- More dirty little secrets of online panel research.; 2012
- Mobile email opens report 2nd half 2011; 2012
- Metering mobile usage. Insights from global Arbitron mobile trends panel; 2012; Verkasalo, H.