CDR Archives — LIRNEasia

By employing unsupervised and supervised machine learning techniques, we explore the feasibility of utilizing mobile call detail records (CDRs) as well as geographic information system (GIS) and remote sensing (RS) data to map poverty spatially
A research paper exploring an alternative approach to address the concern of privacy in sharing big data datasets by generating privacy-preserving artificial call detail records (CDRs) in accordance with the desired macro features of the dataset.
by Keshan de Silva and Yudhanjaya Wijeratne One of the most useful datasets we have is a collection of¬†pseudoanaonymized call data records for all of Sri Lanka, largely from the year 2013. Given that Sri Lanka has extremely high cell coverage and subscription rates (we’re actually oversubscribed – there’s more subscribers than people in the country; an artifact of people owning multiple SIMS), this dataset is ripe for conducting analysis at a big data scale. We recently used it to examine the event attendance of the annual Nallur festival that happens in Jaffna, Sri Lanka. Using CDR records, we were able to analyze the increase in population of the given region during the time of the festival. A lengthy writeup describes it on Medium, explaining the importance of the festival and the logic for picking it.