Big Data- Good Data: Understanding Society by combining survey data and new forms of data

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User-generated data, e.g. social media and crowdsourced data, have provided researchers and decision makers with an unprecedented opportunity to monitor and understand society at much higher frequency and granularity. However, these 'new forms of data' may have some challenges to be considered alongside traditional data, such as randomised surveys. Their huge sample size and questionable quality (e.g. bias, dependencies, representativeness, and missingness) make inferences from traditional statistical and analytical methods questionable. Adjustments are thus needed to ensure biased and unrepresentative data do not lead to flawed conclusions. This project builds on recent work by incorporating geospatial and social components to two main challenges of using user-generated data in social science, i.e. quality-quantity balance, and missing data imputation