Turning Big Data - call logs, mobile-banking transactions, online user-generated content such as blog posts and Tweets, online searches, satellite images, etc. - into actionable information requires using computational techniques to unveil trends and patterns within and between these extremely large socioeconomic datasets. New insights gleaned from such data mining should complement official statistics, survey data, and information generated by Early Warning Systems, adding depth and nuances on human behaviours and experiences - and doing so in real time, thereby narrowing both information and time gaps.
This paper does not offer a grand theory of technology-driven social change in the Big Data era. Rather it aims to delineate the main concerns and challenges raised by “Big Data for Development” as concretely and openly as possible, and to suggest ways to address at least a few aspects of each.
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