BigSurv20 program
Friday 6th November Friday 13th November Friday 20th November Friday 27th November
Friday 4th December
If you would like any of your content to be removed from this program please email: info@bigsurv.org
Friday 6th November
| 10:00 - 11:30 (ET, GMT-5) 7:00 - 8:30 (PT, GMT-8) 16:00 - 17:30 (CET, GMT+1) | Opening and keynote (all live)Moderator: Peter Lugtig (p.lugtig@uu.nl) |
| 11:45 - 13:15 (ET, GMT-5) 8:45 - 10:15 (PT, GMT-8) 17:45 - 19:15 (CET, GMT+1) | Big Data Challenge KickoffModerator: Barry Schouten (jg.schouten@cbs.nl) |
| 11:45 - 13:15 (ET, GMT-5) 8:45 - 10:15 (PT, GMT-8) 17:45 - 19:15 (CET, GMT+1) | Classifieds: Coding open-ended responses using machine learningModerator: Stas Kolenikov (skolenik@gmail.com) Using supervised classification for categorizing answers to an open-ended question on panel participation motivation A framework for using machine learning to support qualitative data coding Training deep learning models with active learning framework to classify “other (please specify)“ comments Measuring the validity of open-ended questions: Application of unsupervised learning methods Writerly Respondents: Explaining Nonresponse and Response Length for Open-Ended Questions |
| 11:45 - 13:15 (ET, GMT-5) 8:45 - 10:15 (PT, GMT-8) 17:45 - 19:15 (CET, GMT+1) | Improving survey questions using machine learning and AIModerator: Katharina Meintinger (k.m.meitinger@uu.nl) Open question formats: Comparing the suitability of requests for text and voice answers in smartphone surveys The sound of respondents: How do emotional states affect the quality of voice answers in smartphone surveys? Automated double-barreled question classification using machine learning Using generative adversarial active learning to identify poor closed-ended survey responses Improving SHARE translation verification |
| 11:45 - 13:15 (ET, GMT-5) 8:45 - 10:15 (PT, GMT-8) 17:45 - 19:15 (CET, GMT+1) | Properties of organic data and their integration with traditional surveysModerator: Peter Lugtig (p.lugtig@uu.nl) Can social media data complement traditional survey data? A reflexion matrix to evaluate their relevance for the study of public opinion. Integrating organic data and designed data for higher quality measurement: Overcoming coverage limitations of big data Towards a total error framework for sensor and survey data Is bigger always better? Evaluating measurement error in organic TV tuning data Multivariate density estimation by neural networks |
| 11:45 - 13:15 (ET, GMT-5) 8:45 - 10:15 (PT, GMT-8) 17:45 - 19:15 (CET, GMT+1) | I'm sensing there's an APP for thatModerator: Bella Struminskaya (b.struminskaya@uu.nl) Using progressive web apps and computer vision to improve mobile data capture efforts Activity trackers in social research: nonresponse and data quality issues Social desirability in digital trace data collection Big data physiologic and ecological monitoring assessments and compliance in a complex, multi-site clinical longitudinal study (AURORA Study) Leveraging what’s there: A new approach to collecting screen time data in the 1970 British Cohort Study |
| 11:45 - 13:15 (ET, GMT-5) 8:45 - 10:15 (PT, GMT-8) 17:45 - 19:15 (CET, GMT+1) | Big brother, big data or both? Protecting privacy in the era of big dataModerator: Don Jang (jang-don@norc.org) Ethical issues in the use of big data for social research The paradox of data sharing and data privacy in the social sciences The challenges of legal analysis, between text mining and machine learning Measuring privacy and accuracy concerns for 2020 census data dissemination |