Demographic research with non-representative internet data
- 7 April 2015
- journal article
- research article
- Published by Emerald in International Journal of Manpower
- Vol. 36 (1), 13-25
- https://doi.org/10.1108/ijm-12-2014-0261
Abstract
Purpose: – Internet data hold many promises for demographic research, but come with severe drawbacks due to several types of bias. The purpose of this paper is to review the literature that uses internet data for demographic studies and presents a general framework for addressing the problem of selection bias in non-representative samples. Design/methodology/approach: – The authors propose two main approaches to reduce bias. When ground truth data are available, the authors suggest a method that relies on calibration of the online data against reliable official statistics. When no ground truth data are available, the authors propose a difference in differences approach to evaluate relative trends. Findings: – The authors offer a generalization of existing techniques. Although there is not a definite answer to the question of whether statistical inference can be made from non-representative samples, the authors show that, when certain assumptions are met, the authors can extract signal from noisy and biased data. Research limitations/implications: – The methods are sensitive to a number of assumptions. These include some regularities in the way the bias changes across different locations, different demographic groups and between time steps. The assumptions that we discuss might not always hold. In particular, the scenario where bias varies in an unpredictable manner and, at the same time, there is no “ground truth” available to continuously calibrate the model, remains challenging and beyond the scope of this paper. Originality/value: – The paper combines a critical review of existing substantive and methodological literature with a generalization of prior techniques. It intends to provide a fresh perspective on the issue and to stimulate the methodological discussion among social scientists.Keywords
This publication has 29 references indexed in Scilit:
- Overcoming the Problems of Inconsistent International Migration data: A New Method Applied to Flows in EuropeEuropean Journal of Population, 2010
- Measuring the impact of health policies using Internet search patterns: the case of abortionBMC Public Health, 2010
- The Social Demography of Internet Dating in the United StatesSocial Science Quarterly, 2010
- Detecting influenza epidemics using search engine query dataNature, 2009
- Bayesian melding for estimating uncertainty in national HIV prevalence estimatesSexually Transmitted Infections, 2008
- Understanding individual human mobility patternsNature, 2008
- Uncovering individual and collective human dynamics from mobile phone recordsJournal of Physics A: Mathematical and Theoretical, 2008
- Who Visits Online Dating Sites? Exploring Some Characteristics of Online DatersCyberPsychology & Behavior, 2007
- Inference for Deterministic Simulation Models: The Bayesian Melding ApproachJournal of the American Statistical Association, 2000
- The central role of the propensity score in observational studies for causal effectsBiometrika, 1983