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Christina Hughes

Bio: Christina Hughes is an academic researcher. The author has contributed to research in topics: Mobile phone & European union. The author has an hindex of 1, co-authored 1 publications receiving 32 citations.


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DOI
01 Jan 2018
TL;DR: In this article, the authors propose a method to solve the problem of homonymity in homonym identification, which is called homonym-based homonymization, or homonymisation.
Abstract: .............................................................................................................. 2

63 citations

Journal ArticleDOI
TL;DR: In this paper, the suitability of Twitter data for measuring post-disaster population mobility using the case of Hurricane Maria in Puerto Rico was examined, and the authors found that 8.3% of resident sample relocated during the months after Hurricane Maria and nearly 4% of were still displaced 9 months later.
Abstract: After a disaster, there is an urgent need for information on population mobility. Our analysis examines the suitability of Twitter data for measuring post-disaster population mobility using the case of Hurricane Maria in Puerto Rico. Among Twitter users living in Puerto Rico, we show how many were displaced, the timing and destination of their displacement, and whether they returned. Among Twitter users arriving in Puerto Rico after the disaster, we show the timing and destination of their trips. We find that 8.3% of resident sample relocated during the months after Hurricane Maria and nearly 4% of were still displaced 9 months later. Visitors to Puerto Rico fell significantly in the year after Hurricane Maria, especially in tourist areas. While our Twitter data is not representative of the Puerto Rican population, it provides broad evidence of the effect of this disaster on population mobility and suggests further potential use.

55 citations

Journal ArticleDOI
24 Oct 2019-PLOS ONE
TL;DR: The feasibility of using non-traditional data sources to fill existing gaps in migration statistics and comparing them with data from reliable sources is investigated, finding that FN-derived migration estimates can be used for trend analysis and early-warning purposes.
Abstract: Quantifying global international mobility patterns can improve migration governance. Despite decades of calls by the international community to improve international migration statistics, the availability of timely and disaggregated data about long-term and short-term migration at the global level is still very limited. In this study, we investigate the feasibility of using non-traditional data sources to fill existing gaps in migration statistics. To this end, we use anonymised and publicly available data provided by Facebook’s advertising platform. Facebook’s advertising platform classifies its users as “lived in country X” if they previously lived in country X, and now live in a different country. Drawing on statistics about Facebook Network users (Facebook, Instagram, Messenger, and the Audience Network) who have lived abroad and applying a sample bias correction method, we estimate the number of Facebook Network (FN) “migrants” in 119 countries of residence and in two time periods by age, gender, and country of previous residence. The correction method estimates the probability of a person being a FN user based on age, sex, and country of current and previous residence. We further estimate the correlation between FN-derived migration estimates and reference official migration statistics. By comparing FN-derived migration estimates in two different time periods, January-February and August-September 2018, we successfully capture the increase in Venezuelan migrants in Colombia and Spain in 2018. FN-derived migration estimates cannot replace official migration statistics, as they are not representative, and the exact methods the FN uses for classifying its users are not known, and might change over time. However, after carefully assessing the validity of the FN-derived estimates by comparing them with data from reliable sources, we conclude that these estimates can be used for trend analysis and early-warning purposes.

50 citations

Posted Content
TL;DR: A striking relationship between the negative variation of mobility flows and the net reproduction number is found and the value of "big" mobility data to the monitoring of key epidemic indicators to inform choices as the epidemics unfolds in the coming months.
Abstract: In 2020, countries affected by the COVID-19 pandemic implemented various non-pharmaceutical interventions to contrast the spread of the virus and its impact on their healthcare systems and economies. Using Italian data at different geographic scales, we investigate the relationship between human mobility, which subsumes many facets of the population's response to the changing situation, and the spread of COVID-19. Leveraging mobile phone data from February through September 2020, we find a striking relationship between the decrease in mobility flows and the net reproduction number. We find that the time needed to switch off mobility and bring the net reproduction number below the critical threshold of 1 is about one week. Moreover, we observe a strong relationship between the number of days spent above such threshold before the lockdown-induced drop in mobility flows and the total number of infections per 100k inhabitants. Estimating the statistical effect of mobility flows on the net reproduction number over time, we document a 2-week lag positive association, strong in March and April, and weaker but still significant in June. Our study demonstrates the value of big mobility data to monitor the epidemic and inform control interventions during its unfolding.

40 citations

Journal ArticleDOI
21 Feb 2020-PLOS ONE
TL;DR: This paper proposes to use Facebook’s advertising platform as an additional data source for monitoring the ongoing crisis in Venezuela and estimates and validate national and sub-national numbers of refugees and migrants and break-down their socio-economic profiles to further understand the complexity of the phenomenon.
Abstract: Venezuela is going through the worst economical, political and social crisis in its modern history. Basic products like food or medicine are scarce and hyperinflation is combined with economic depression. This situation is creating an unprecedented refugee and migrant crisis in the region. Governments and international agencies have not been able to consistently leverage reliable information using traditional methods. Therefore, to organize and deploy any kind of humanitarian response, it is crucial to evaluate new methodologies to measure the number and location of Venezuelan refugees and migrants across Latin America. In this paper, we propose to use Facebook's advertising platform as an additional data source for monitoring the ongoing crisis. We estimate and validate national and sub-national numbers of refugees and migrants and break-down their socio-economic profiles to further understand the complexity of the phenomenon. Although limitations exist, we believe that the presented methodology can be of value for real-time assessment of refugee and migrant crises world-wide.

31 citations