Web Survey Bibliography
Title Online and Social Media Data As an Imperfect Continuous Panel Survey
Author Diaz, F.; Garmon, F.; Hofman, J. K.; Kiciman, E.; Rothschild, D.
Source PLOS one, 11, 1
Year 2016
Database ProQuest
Access date 06.02.2016
Full text pdf (889 KB)
Abstract There is a large body of research on utilizing online activity as a survey of political opinion to predict real world election outcomes. There is considerably less work, however, on using this data to understand topic-specific interest and opinion amongst the general population and specific demographic subgroups, as currently measured by relatively expensive surveys. Here we investigate this possibility by studying a full census of all Twitter activity during the 2012 election cycle along with the comprehensive search history of a large panel of Internet users during the same period, highlighting the challenges in interpreting online and social media activity as the results of a survey. As noted in existing work, the online population is a non-representative sample of the offline world (e.g., the U.S. voting population). We extend this work to show how demographic skew and user participation is non-stationary and difficult to predict over time. In addition, the nature of user contributions varies substantially around important events. Furthermore, we note subtle problems in mapping what people are sharing or consuming online to specific sentiment or opinion measures around a particular topic. We provide a framework, built around considering this data as an imperfect continuous panel survey, for addressing these issues so that meaningful insight about public interest and opinion can be reliably extracted from online and social media data.
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ProQuest (Abstract) / (Full text)
Year of publication2016
Bibliographic typeJournal article
Web survey bibliography - 2016 (264)
- A Statistical Approach to Provide Individualized Privacy for Surveys; 2016; Esponda, F.; Huerta, K.; Guerrero, V. M.
- 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.
- A multi-group analysis of online survey respondent data quality: Comparing a regular USA consumer panel...; 2016; Golden, L.; Albaum, G.; Roster, C. A.; Smith, S. M.
- Does the Inclusion of Non-Internet Households in a Web Panel Reduce Coverage Bias?; 2016; Eckman, S.
- Investigating respondent multitasking in web surveys using paradata; 2016; Sendelbah, A.; Vehovar, V.; Slavec, A.; Petrovcic, A.
- The effect of email invitation elements on response rate in a web survey within an online community; 2016; Petrovcic, A.; Petric, G.; Lozar Manfreda, K.
- Respondent Conditioning in Online Panel Surveys: Results of Two Field Experiments; 2016; Struminskaya, B.
- Presentation matters: how mode effects in item non-response depend on the presentation of response options...; 2016; Zeglovits, E.; Schwarzer, S.
- Internet-administered Health-related Quality of Life Questionnaires Compared With Pen and Paper in an...; 2016; Nitikman, M.; Mulpuri, K.; Reilly, C. W.
- Doing Surveys Online ; 2016; Toepoel, V.
- Exploring Factors in Contributing Student Progress in the Open University; 2016; Arifin, M. H.
- Use of Smartphones as a New Survey Mode: A Feasibility Study ; 2015; Hu, S.; Freedner-Maguire, N.; Dayton, J.; Neff, L.
- Using Text-to-Speech (TTS) for Audio-CASI; 2012; Couper, M. P., Kirgis, N., Buageila, S., Berglund, P.