BigSurv18 program
Wednesday 24th October Thursday 25th October Friday 26th October Saturday 27th October
Friday 26th October
| 08:00 - 18:30 Room: 30.SV01 HALL | Registration and Information Desk | ||||||||||||||
| 08:30 - 17:30 Room: 30.S02 S. Expo | Posters 1 (actively presented from 11.30 to 13.00)These posters are the result of the Barcelona Dades Obertes Data Challenge organized by the city of Barcelona. For more information on the institutions and the data challenge please see:
Chair: Antje Kirchner (RTI) Count Regression Modelling on Number of Migrants in Households Testing Analytical Methods Related With the Unstructured Data Analysis From Perspective of 'Data Scientists and Methodologists' A Joint Modelling Approach in SAS to Assess Association Between Adult and Child HIV Infections in Kenya Comparison of Artificial Neural Networks and Generalized Linear Models for NBA Outcomes From Data Points to Data Dan: Combining Log Analysis: Survey Analysis and Interviews to Segment Google Analytics Customers SurveyMotion: What Can We Learn From Sensor Data About Respondents' Actions in Mobile Web Surveys? Measuring the Official Statistics Capability of the Public-Sector Organizations in Presence of Big Data Sources Spatial Influence in Basque Country's Hotels Price Recognizing Patterns in the Price Time-Series of the Basque Country Hotels A Cross-Sectional vs. Longitudinal Case Study of Twitter and Presidential Approval Developing an Effective Procurement Performance Data Approach for Predicting Expectations Gaps in Construction Contracts at District Local Governments In Uganda Income Inequality Through People's Lenses: Evidence From the OECD Compare Your Income Web-Tool | ||||||||||||||
| 08:30 - 09:30 Room: 30.S01 Auditori | Plenary: Big Data, Surveys and the Privacy-Ethics Challenge: An Interdisciplinary Panel DiscussionThis special plenary session on "Big Data, Surveys and the Privacy-Ethics Challenge: An Interdisciplinary Panel Discussion," is organized and moderated by Dr. Frauke Kreuter. The plenary features Dr. Julia Lane, a professor at the NYU Center for Urban Science and Progress; Bianca Marcu, the advocacy and standards services coordinator at ESOMAR; and Dr. Karsten Weber, an expert with a background in computer science and ethics who focuses, particularly on the ethics of technology, information ethics, and the Internet’s social impacts.For more information on - Dr. Frauke Kreuter, please visit: http://sswml.uni-mannheim.de/Team/Frauke Kreuter/ - Dr. Julia Lane, please visit: http://www.julialane.org/ - Bianca Marcu, please visit: https://www.linkedin.com/in/bianca-marcu-273893133/ - Dr. Karsten Weber, please visit: https://hps.hs-regensburg.de/wek39793/doku.php?id=en:about Chair: Frauke Kreuter (IAB, University of Mannheim, University of Maryland) | ||||||||||||||
| 08:00 - 20:30 Room: 40.033 | Nursing Room available | ||||||||||||||
| 09:30 - 09:45 Room: 30.S02 S. Expo | Break | ||||||||||||||
| 09:45 - 11:15 Room: 40.004 | Classifieds: Coding Open-Ended Responses Using Machine Learning MethodsChair: Malte Schierholz (Institute for Employment Research (IAB)) Automated Topic Modeling for Trend Analysis of Open-Ended Response Data Natural Language Processing for Open-Ended Survey Questions Automatic Classification of Open-Ended Questions: Check-All-That-Apply Questions Democracy in Writing: Comparing the Meaning of Democracy in Open-Ended Survey Responses and in Big Online Text Data | ||||||||||||||
| 09:45 - 11:15 Room: 40.008 | Peering through Transition Lenses: New Landscapes and Horizons for Survey Research and Social ScienceChair: Zeeshan-ul-hassan Usmani (MiSK Foundation) The Future Is Now: How Surveys Can Harness Social Media to Address 21st-Century Challenges New Paradigms in Online Declarative Data Collection Mixed Methods Approaches to Programmatic Social Science Research in Applied Setting Statistical Inference Aided by Big Data | ||||||||||||||
| 09:45 - 11:15 Room: 40.105 | Leveraging Big Data for Improving Health Research… the Initial VisitChair: Charlie Knott (RTI International) Mapping Behavioral Influencers in the Pharmaceutical Industry Predicting Depression Occurrence Using Classification Algorithm in Data Mining Assessing Community Health Using Imagery From Google Street View Smartphone Interrupted Sleep: A New Public Health Challenge? High-Resolution Smartphone Data From Denmark | ||||||||||||||
| 09:45 - 11:15 Room: 40.109 | Big Data, Little Error? Assessing the Total Error of Survey Estimates in the Era of Big DataChair: Ashley Amaya (RTI International) Total Error Frameworks for Hybrid Estimation and Their Applications Understanding the Effects of Record Linkage on Estimation of Total When Combining a Big Data Source With a Probability Sample Income Data Linkage in the Swiss Context: What Can We Learn Regarding Different Error Sources? Combining Administrative Data and Survey Samples for the Intelligent User | ||||||||||||||
| 09:45 - 11:15 Room: 40.213 | More Than Words Can Say: Leveraging Data Science Methods to Get the Full Story about Survey RespondentsChair: Gabriele Durrant (University of Southampton) Combining High-Volume Paradata With Survey Data to Understand Respondent, Instrument, and Interviewer Effects on Response Latencies Eight Seconds From Opine to Click - Respondent and Question Effects on Response Times in a Large-Scale Web Panel Using Paradata to Interpret an Autoforward Experiment Research-Driven Product Development With Surveys, Big Data, and Machine Learning: A Google AdWords Case-Study | ||||||||||||||
| 09:45 - 11:15 Room: 40.035 S. Graus | Are the Machines Making the Mark? Applications to Compare Traditional and Machine Learning ModelsChair: Curtis Signorino (University of Rochester) Empirical Comparison of Time Series Data Mining Algorithms Real-Time Estimation of Unemployment With Dynamic Factor and Time-Varying State Space Models Machine-Learning Techniques for Family Demography: An Application to the Divorce Determinants in Germany Comparison of Simple and Complex Predictive Models Applied to the National Surveys on Drug Use and Health. Example of Multiple Visits to Emergency Departments. | ||||||||||||||
| 11:15 - 11:30 Room: 30.S02 S. Expo | Coffee Break | ||||||||||||||
| 11:30 - 13:00 Room: 40.105 | Big Data Enhancements to Surveys: Methods and ToolsChair: Niklas M. Loynes (NYU / University of Manchester) When Behavioral Data Isn't Enough: Mixing Survey, Log, and Usability Data for a Holistic Understanding of User Experience Using a Large GPS Dataset to Enhance Survey Matching A Case Study of Processing Large Scale Data - A Method to Accomplish Reproducibility | ||||||||||||||
| 11:30 - 13:00 Room: 40.109 | Ok Google - Is Siri Busy? Innovating With Mobile Phone Data?Chair: Annette Jäckle (University of Essex) Performance and Sensitivities of Home Detection on Mobile Phone Data More Than Meets the Eyes: Complementing Surveys With Mobile Phone Digital Data Trail Methodological Implications of Device-Related Error Sources in Integrating Smartphone Sensor Data and Survey Data Complementing Official Statistics With Mobile Phone Data Mobile Phone Data for Official Statistics: Elements for a Production Framework | ||||||||||||||
| 11:30 - 13:00 Room: 40.150 | Ethical Considerations for Using Big Data I: Exploring the Ethics of Data LinkageChair: Henning Silber (GESIS - Leibniz Institute for the Social Sciences) Attitudes Towards Data Linkage, Privacy, Ethics, and the Potential for Harm Public Confidentiality Expectations Regarding Data Linkage Evaluating Survey Consent to Social Media Linkage Privacy-Preserving Methods for Linking Big Data and Survey Data Sets Determinants of Consent to Administrative Records Linkage in Next Steps - A Large-Scale Longitudinal Cohort Study in the U.K. | ||||||||||||||
| 11:30 - 13:00 Room: 40.154 | Putting Text into Context: Exploring Classification and Automation of Textual Survey DataChair: Matthias Schonlau (University of Waterloo) A comparison of automatic algorithms for occupation coding How to Make AI do Your Job for Statistical Classification of Industry and Occupation Topic Modeling and Status Classification Using Data From Surveys and Social Networks Machine Learning and Verbatim Survey Responses: Classification of Criminal Offences in the Crime Survey for England and Wales | ||||||||||||||
| 11:30 - 13:00 Room: 40.213 | Computers vs. Humans: Who's Better at Social Science?Chair: Masahiko Aida (Civis Analytics) Data-Inspired Life - How Data Science and AI is Pushing the Boundaries of Human Behavior Can Computers Compete With Human Experience? Detecting and Comparing Survey Research Topics in Conference and Journal Abstracts | ||||||||||||||
| 11:30 - 13:00 Room: 40.035 S. Graus | Population Estimates for Small Geographic Areas: Can We Do a Better Job?Conducting surveys in developing countries is particularly challenging because many areas lack a complete sampling frame, have outdated census information, or have limited data available for designing and selecting a representative sample. With developments in GIS, remote sensing, and machine learning, tools have emerged to disaggregate and update the distribution of census data to support survey sampling methodology and improve population estimates. For this session, a mix of current developers and users of massive global population datasets will discuss the basis for these population estimates, scope, and limitations. We will also present tools and approaches for utilizing these geo-referenced population estimates for complex household survey sampling (i.e., Geo-sampling and GridSample). Lastly, we will discuss challenges with geographic population distributional assumptions within these areas that are operationally relevant for conducting household surveys, with approaches to help address them using deep neural network models and sample based estimates.Chair: Safaa Amer (RTI International) Advances in Gridded Population Distribution Databases: LandScan HD GridSample.org: Generating Household Survey Sampling Units From Gridded Population Data Residential Scene Classification for Geo-Sampling in Developing Countries Using Deep Convolutional Neural Networks on High-Resolution Satellite Imagery Household Detection Within Gridded Population Area Units: Producing Small Area Population Estimates in Geo-Sampling | ||||||||||||||
| 13:00 - 14:15 Room: 30.S02 S. Expo | Lunch | ||||||||||||||
| 14:15 - 15:45 Room: 40.002 | Methods to Improve Survey Representativeness Using High Dimensional DataThe explosion of "big data" in the 21st Century has led some researchers to declare the end of the traditional probability sample paradigm. We propose three talks that refute that belief, and discusses methods to leverage the strengths of high dimensional data, either from probability or nonprobability samples, with the strengths of more traditional survey data.Chair: Michael Elliott (University of Michigan) Calibrating Big Data for Population Inference: Applying Quasi-Randomization Approach to Naturalistic Driving Data Using Bayesian Additive Regression Trees Bayesian Inference for Sample Surveys in the Presence of High-Dimensional Auxiliary Information How Non-Ignorable is the Selection Bias in Nonprobability Samples? An Illustration of New Measures Using a Large Genetic Study on Facebook Evaluating Doubly Robust Estimation for Online Opt-In Samples With Bayesian Additive Regression Trees | ||||||||||||||
| 14:15 - 15:45 Room: 40.105 | Big Data for Official Statistics I: Big Data Use is Officially a Big Deal for Government StatisticsChair: Lars Lyberg (Inizio) Big Data Initiatives in Official Statistics A Framework for Big Data in Official Statistics Mining the New Oil for Official Statistics Enhancing U.S. Federal Statistics by Combining Multiple Data Sources | ||||||||||||||
| 14:15 - 15:45 Room: 40.109 | Smart TVs, Smartphones, and now Smart Surveys: Building Smarter Surveys Using Big Data ToolsChair: Stas Kolenikov (Abt Associates) Augmenting Surveys: An Efficient Framework for the Storing, Querying, and Processing of Big Survey Data Comparing Coding of Interviewer Question-Asking Behaviors Using Recurrent Neural Networks to Human Coders The ODISSEI Data Platform | ||||||||||||||
| 14:15 - 15:45 Room: 40.150 | Ethical Considerations for Using Big Data II: Exploring the Relationship between Ethical Considerations, Reproducibility, and ParticipationChair: Rebecca Powell (RTI International) Justice Rising - The Growing Ethical Importance of Big Data, Survey Data, Models, and AI Download presentation 2 Reproducibility in the Era of Big Data: Lessons for Developing Robust Data Management and Data Analysis Procedures Big Data's Front-Ended Ethical Considerations Ignore How Results Can Stigmatize Identifiable Groups: Examining Big Wastewater Data in New Zealand Enriching an Ongoing Panel Survey With Mobile Phone Measures: The IAB-SMART App Augmenting Survey Data With Big Data: Is There a Threat to Panel Retention? | ||||||||||||||
| 14:15 - 15:45 Room: 40.213 | Big Data Methods, Small Survey Nonresponse?Chair: Roeland Beerten (Statistics Flanders) Advances in Modelling Attrition: The Added Value of Paradata and Machine Learning Algorithms Preserving our Precious Respondents: Predicting and Preventing Non-Response and Panel Attrition by Analyzing and Modeling Longitudinal Survey and Paradata Using Data Science Techniques Using Predictive Modeling to Identify Panel Dropouts Operational Challenges in Gaining and Maintaining Survey Respondents' Cooperation to Supplement Survey Data with "Big Data" Collected Through a Custom Smartphone Application | ||||||||||||||
| 14:15 - 15:45 Room: 40.035 S. Graus | Missing Data? No Big Deal Using New Big Data MethodsChair: Paul Biemer (RTI International) Motivated Misreporting in Crowdsourcing Tasks of Content Coding, Image Classification, and Surveys New Data to Correct for Nonresponse Bias: The Case of Administrative Data in Spain Health Survey Non-Representativeness Bias Methodology and Validation Experiences in FBI's NCS-X NIBRS Estimation Project | ||||||||||||||
| 15:45 - 16:00 Room: 30.S02 S. Expo | Coffee Break | ||||||||||||||
| 16:00 - 17:30 Room: 40.105 | Big Data for Official Statistics II: Administrative and Big Data Use for Survey Design and EstimationChair: Lilli Japec (Statistics Sweden) Web Scraping Meets Survey Design: Combining Forces Download presentation Making Administrative Records Key to Operational Agility for the American Community Survey Linkage of the Australian Census to Three Administrative Databases With an Application to Understanding Income Inequality in Australia Use of Alternative Data Sources at Statistics Canada: A Case Study With GPS Data The Usability of Government Open Data for Social Research - Estonian Case | ||||||||||||||
| 16:00 - 17:30 Room: 40.109 | Filing the Claim for Social Media Data: Who's Covered and Who Isn'tChair: Jonathan Nagler (NYU, Social Media and Political Participation Lab) Seeking the "Ground Truth": Assessing Methods Used for Demographic Inference From Twitter Coverage Bias in Election Research Using Data From Social Media Who's Tweeting About the President? What Big Survey Data Can Tell Us About Digital Traces Augmenting Public Opinion Research With Social Media Data: A Case Study of Brexit | ||||||||||||||
| 16:00 - 17:30 Room: 40.213 | Exploring How Responsive Designs Respond to Machine Learning MethodsChair: Gonzalo Rivero (Westat) Responsive Designs in Practice Machine Learning in Adaptive Survey Designs: A Bandit Approach Mining Interviewer Observations in a Panel Survey Predicting Response Mode Preferences of Survey Respondents: A Comparison Between Traditional Regression and Data Mining Methods | ||||||||||||||
| 16:00 - 17:30 Room: 40.248 | The Fourth Paradigm: Moving From Computational Science to Data-Intensive Scientific Discovery?Chair: Craig Hill (RTI International) Moving Social Science Into the Fourth Paradigm: Opportunity Abounds Doing Social Science With Big Data Sets - A Framework of Approaches A Paradigm Shift From Surveys to Big Data in Financial Market Research Addressing the Variety and Changeability of Big Data From Data to Big Analytics- Automated Analytic Platforms for Data Exploration Download presentation 2 | ||||||||||||||
| 16:00 - 17:30 Room: 40.250 | Getting Aggressive about Passive Data CollectionChair: Stephanie Eckman (RTI International) Combining Survey and Wearable Data on Exercise and Sleep Using Call Detail Records to Conduct a Commuting Survey in Poland Capture-Recapture Techniques for Transport Survey Estimate Adjustment Using Road Sensor Data A New Smart Meter Research Portal | ||||||||||||||
| 16:00 - 17:30 Room: 40.035 S. Graus | Respondents Responding Well or So I Recall… Exploring Memory, Mode, and Behaviour in SurveysChair: Linsay Gray (MRC/CSO Social & Public Health Sciences Unit, University of Glasgow) Different Strokes for Different Folks: An Assessment of Mode Effects in a Student Population Memory Bookmarking: Using Multimodal Real-Time Data to Facilitate Recall What Are the Effects of "Forcing" Respondents to Behave in Certain Ways? | ||||||||||||||
| 19:00 - 21:30 Room: Maritim Restaurant | Conference Dinner at Maritim Restaurant, Moll d'Espanya, 4, 08039, +34 932 211 775 |