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Big Data for Good Can Big Data Illustrate the Challenges Facing Syrian Refugees in Lebanon? © 2020 United Nations All Rights Reserved Worldwide

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Big Data for Good Can Big Data Illustrate the Challenges Facing Syrian Refugees in Lebanon? © 2020 United Nations All Rights Reserved Worldwide 1 0 0 1 1 Big Data for Good 0 Can Big Data Illustrate the Challenges Facing Syrian 0Refugees in Lebanon? 1 VISION ESCWA,an innovative catalyst for a stable, just and flourishing Arab region MISSION Committedto the 2030 Agenda, ESCWA’s passionate team produces innovative knowledge,fosters regional consensus and delivers transformational policy advice. Together, we work for a sustainable future for all. Big Data for Good Can Big Data Illustrate the Challenges Facing Syrian Refugees in Lebanon? © 2020 United Nations All rights reserved worldwide Photocopies and reproductions of excerpts are allowed with proper credits. All queries on rights and licenses, including subsidiary rights, should be addressed to the United Nations Economic and Social Commission for Western Asia (ESCWA), e-mail: [email protected]. The findings, interpretations and conclusions expressed in this publication are those of the authors and do not necessarily reflect the views of the United Nations or its officials or Member States. The designations employed and the presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of the United Nations concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Links contained in this publication are provided for the convenience of the reader and are correct at the time of issue. The United Nations takes no responsibility for the continued accuracy of that information or for the content of any external website. References have, wherever possible, been verified. Mention of commercial names and products does not imply the endorsement of the United Nations. References to dollars ($) are to United States dollars, unless otherwise stated. Symbols of United Nations documents are composed of capital letters combined with figures. Mention of such a symbol indicates a reference to a United Nations document. United Nations publication issued by ESCWA, United Nations House, Riad El Solh Square, P.O. Box: 11-8575, Beirut, Lebanon. Website: www.unescwa.org. Photo credits: Page 13: Eliane29 Page 15: verve231 Page 16: alexkuehni Page 21: dinosmichail 0 Page 27: brightstars Page 28: Aleksandr_Vorobev Page 29: bombuscreative Page 30: verve231 Page 32: artiemedvedev Page 34: Joel Carillet Page 38: Joel Carillet Page 43: ridvan_celik Page 47: Joel Carillet Page 51: Orbon Alija. BIG DATA FOR GOOD - CAN BIG DATA ILLUSTRATE THE CHALLENGES FACING SYRIAN REFUGEES IN LEBANON? Acknowledgements We would like to acknowledge the productive partnerships with the Data-Pop Alliance and the Lebanon Central Administration of Statistics (CAS). The contributions of our colleagues at the HBKU Qatar Computing Research Institute (QCRI) and UNHCR Lebanon are very much appreciated. On behalf of all the partners, we wish to express our appreciation for the Ministry of Communications in Lebanon for making the Mobile Call Detail Records available for the project team through CAS as custodian of data. The management of data access, processing and storage was guided by clear principles agreed to with the multi-disciplinary CODE (Council for the Orientation for Development and Ethics) members. 0 0 1 3 BIG DATA FOR GOOD - CAN BIG DATA ILLUSTRATE THE CHALLENGES FACING SYRIAN REFUGEES IN LEBANON? Table of contents Acknowledgements 3 Key Messages 7 Introduction 12 I. Brief Presentation of the Data Sources 14 A. Non-traditional data sources: Big data sources 15 B. Additional data sources: Ground-truthing 16 II. Methodology 18 III. Data Sources and Approaches 20 A. Call detail records 21 B. Facebook Ad Platform 27 C. Global Database of Events, Language, and Tone (GDELT) 31 D. Twitter 36 IV. Predictive Capacity of Data Sources with Ground Truth Data 40 A. Linear univariate and multivariate regression 41 V. Discussion 46 VI. Lessons Learned and Recommendations 50 A. Enabling conditions crucial to project success 51 B. Privacy-conscientious design 51 C. Accessing call detail records 51 Annex 52 5 BIG DATA FOR GOOD - CAN BIG DATA ILLUSTRATE THE CHALLENGES FACING SYRIAN REFUGEES IN LEBANON? Key Messages Introduction 2011 5 million As of 2011, over 5 million Syrians have fled their native land, seeking refuge in different countries. The living and social conditions of these refugees and their host communities have recurrently featured as a priority on the policy agendas of the humanitarian and development communities, in addition to decision makers in host countries. The socioeconomic challenges resulting from the massive and protracted influx of refugees have overwhelmed access to essential services (such as access to health care, schooling, water VULNERABLE and sanitation) for both refugee and host communities, which in turn have further increased vulnerabilities and worsened conditions. These vulnerabilities are further aggravated by other shocks such as the pandemic and the resulting socioeconomic hardships on host countries. In facing these challenges, policymakers and TRADITIONAL development and humanitarian practitioners rely on traditional data sources from official sources to inform their decisions with regards to both host communities as DATA SOURCES well as Syrian refugees. These sources, such as censuses and surveys, pose a few problems in this context. They can be costly, time-consuming and difficult to collect, and might be inaccurate. Also, they are infrequently updated, which can make the information they contain obsolete, especially within the highly volatile political and socioeconomic context of the Arab region. Policymakers Costly Time- Difficult Inaccurate must be able to offer timely and quick responses to consuming to collect the fast-paced and evolving challenges and crises experienced by refugees and their hosts. THEY ARE INFREQUENTLY UPDATED 7 A question then arises: are there other data sources that could be utilised by policymakers in crisis conditions? With the advent of the ‘Data Revolution’, we are currently surrounded by a wealth EXTRACT PATTERNS, INSIGHTS, of information, known as “Big Data”. RECOMMENDATIONS & SOLUTIONS Vast amounts of data are examined in order to extract patterns and insights, and recommendations and solutions are then formulated accordingly. Big Data Recently, policymakers have started to appreciate the potential use of big data to complement traditional sources of data for policymaking. This pilot project explores the potential of unconventional data sources in informing policymakers of the conditions and vulnerabilities of Syrian refugees and Lebanese host communities. Findings Demographic Status Facebook data indicates that there Phone calling activities suggest that the male population is around 6 times are 2 to 3 times more male users larger than the female population. Official statistics have males and females registered than female users (2019). being on par demographically in 2018. The explanation for this discrepancy is that men are handling the registration of most phone lines for female family members. CULTURAL FACTORS SUPPORT THE INTERPRETATION OF THE ABOVE DATA. Economic Status CALLS DURATION INTERNET TRIPOLI/AKKAR= 0.85 TRIPOLI/AKKAR= 0.97 SYRIAN REFUGEES HOST COMMUNITIES Facebook registration suggests that Syrian refugees and The annual (2016-2019) average duration of calls in Tripoli is host communities have similar high school attainment, approximately 85 per cent of the average duration of calls with a gap of less than 1 per cent. At higher education in Akkar (Tripoli’s internet consumption is 97 per cent of levels, the host community has 5 per cent higher Akkar’s). Syrian refugees’ activities display informal work attainment than refugees (in 2019). Despite the relatively behaviour (weekday and weekend calling activity do not small gap in educational attainment, refugees are much differ much). This supports the belief that Syrian refugees are worse off economically than the host population. participating in informal work (such as farming) in Akkar. 8 BIG DATA FOR GOOD - CAN BIG DATA ILLUSTRATE THE CHALLENGES FACING SYRIAN REFUGEES IN LEBANON? Social Status AR EN 9% 49% 86% Scraping social media platforms and news articles The number of articles in Arabic covering Syrian refugees revealed an increase in hostility towards issues related to fell by 49 per cent between 2016 and 2019. On the other Syrian refugees (negative rating increased by 9 per cent hand, the number of articles in English covering the same between 2017 and 2019 in a sample of 1054 Arabic articles topic increased by 86 per cent. on refugee-related incidents). Local Community tensions are growing steadily and with time these tensions can become dangerous. Security & Mobility Patterns ZGHARTA BECHARRE 7% DECREASED 2% ZAHLE SYRIA WEST BEKAA 8% The proportion of Syrian refugees in the North and Bekaa decreased annually by 2 per cent (based on 2017-2019 Tawasol mobile calling data). This decrease could be As deduced from mobile call activities, the population attributed to the return of refugees to Syria and coincides of the municipalities of Becharre, Zahle and Zgharta with an increase of 80 per cent in English articles covering increased by approximately 7 per cent during 2017, which the return of Syrian refugees to their homeland. could be due to the flow of Syrian refugees into these municipalities. Following an incident when a Lebanese woman was raped and murdered by a Syrian refugee in 2017, local population decreased by 8%. At that time, the population instead began increasing in
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