Web Survey Bibliography
Behavioral economics tells us that emotions can profoundly affect individual behavior and decision-making. Does this also apply to societies at large, i.e. can societies experience mood states that affect their collective decision making? By extension is the public mood correlated or even predictive of economic indicators? Here we investigate whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time. We analyze the text content of daily Twitter feeds by two mood tracking tools, namely OpinionFinder that measures positive vs. negative mood and Google-Profile of Mood States (GPOMS) that measures mood in terms of 6 dimensions (Calm, Alert, Sure, Vital, Kind, and Happy). We cross-validate the resulting mood time series by comparing their ability to detect the public's response to the presidential election and Thanksgiving day in 2008. A Granger causality analysis and a Self-Organizing Fuzzy Neural Network are then used to investigate the hypothesis that public mood states, as measured by the OpinionFinder and GPOMS mood time series, are predictive of changes in DJIA closing values. Our results indicate that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions but not others. We find an accuracy of 86.7% in predicting the daily up and down changes in the closing values of the DJIA and a reduction of the Mean Average Percentage Error (MAPE) by more than 6%.
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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.