Date of Award

12-2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Engineering and Sciences

First Advisor

Eraldo Ribeiro

Second Advisor

Ivica Kostanic

Third Advisor

Ronaldo Menezes

Fourth Advisor

Philip Bernhard

Abstract

Many real-world phenomena have recently been witnessed, motivating scientists to provide a comprehensive understanding of worldwide networks, such as the human migration phenomenon. Human migration research is multidisciplinary and has yielded work in social sciences, physics, and the new field of smart city designing and planning based on big data analytics. The importance of the research comes from the impacts on both countries, sources, and distention. Impacts occur at several levels such as economy, city planning, politics, and law enforcement, leading to changes in demographics. Thus, studies on human migration help policymakers prepare and handle crises when they occur in professional matters. However, the data on migration are limited and mostly outdated. Statistics and numbers on human migration are collected using traditional methods, which rely on governments and agencies around the globe. The three main issues with traditional methods are slowness, cost, and overdue status. This dissertation contributes to the growing body of knowledge in social sensing and network science and shows that perspectives on migration as reflected in social media can be used as a proxy for reality. Our research focuses on the ability to catch streaming data on human migration in real-time using the social media platform Twitter. The Twitter API is used to track the perspectives of users on human migration. By tracking the most common keywords related to migration, we collected a large amount of data. The keywords, which include migrants, refugees, immigrants, and asylum, to name a few, are in eight languages. The main contribution is using Twitter data as an alternative source of information that helps governments and policymakers prepare during crises. In this research, we provide an infrastructure of data that is collected and analyzed scientifically. Finally, our methodology includes overhauling the drawbacks to produce fast, less costly, and up-to-date information.

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