Using Call Detail Records and Sentiment Analysis to Analyze the Development Challenges Faced by Syrian Refugees and Host Communities in Lebanon

Since the beginning of the Syrian civil war in 2011, over 5 million Syrians have fled Syria, seeking refuge in different countries, including Lebanon. With more than one million Syrian refugees, Lebanon has the highest per capita proportion of Syrian refugees in the world. This places an enormous pressure on the country’s essential services for both refugee and host communities, which in turn has further worsened conditions and increased vulnerabilities and risks of tension. In facing these challenges, policymakers and development and humanitarian practitioners rely on traditional data sources from official sources to inform their decisions with regards to both host and refugee communities. These sources can be costly, time-consuming and infrequently updated, which raises the question of the availability of other data sources that could be utilized by policymakers in crisis condition. With the advent of the Data Revolution, we are currently surrounded by a wealth of information, known as Big Data. Our pilot project, in partnership UN-ESCWA, explores the potential of non-traditional big data sources in informing policy makers of the conditions and vulnerabilities of Syrian refugees and Lebanese host communities.