Big Policy Canvas Research Roadmap

[...] * Kim et al. (2016) propose a new method of survey data integration using fractional imputation, and Park et al. (2017) use a measurement error model to combine information from two independent surveys. Further, Kim and Wang (2018) propose two methods of reducing the selection bias associated with the big data sample. Finally, Tufekci (2014) provides a set of practical steps aimed at mitigating the issue of representativeness, including: targeting non-social dependent variables, establishment of baseline panels to study people’s behaviour, use of multidisciplinary teams and multimethod/multiplatform analysis.
Shefali Virkar
This is an emerging research domain that warrants further examination.
Shefali Virkar, 30/09/2019 14:21