WE ARE RECRUITING! Doctoral student with an interest in Big Data analytics, human mobility & social interaction

Are you interested in geoinformatics, big data and social media analytics? Are you curious about the phenomena of human mobility, cross-border mobilities and social interactions of people and transnational people? If yes, check this open four-year doctoral student position at the Digital Geography Lab starting from March 2021 or as agreed with the selected applicant!

We are looking for an enthusiastic, innovative, and highly motivated doctoral student with strong technical knowledge and skills to join our interdisciplinary research group Digital Geography Lab and work in the Academy of Finland-funded project BORDERSPACE – Tracing Interactions and Mobilities Beyond State Borders: Towards New Transnational Spaces.

The doctoral project has three objectives. First, to develop methodologies for quantifying human mobility and activity spaces across country borders based on social media data (Twitter). Second, to develop quantitative methodologies for uncovering activity practices of social media users and their feeling of belonging based on the content of their social media posts. Third, to conduct critical research on dynamic cross-border mobility flows derived from big data, integration of transnational people through their cross-border mobilities and social interactions, and how these are influenced by external factors such as the COVID-19 pandemic.

The successful applicant is expected to have strong fluency in programming (Python or R), experience in advanced spatial analytics and/or social media content analysis, and has worked with big data sources such as mobile phone, smart card and social media data. Prior experience in publishing research in academic journals, participating in research community and having a network of international scholars is an asset.

Read more about the position announcement and apply HERE. The deadline is January 31st 2021.

For further information, please contact Academy Research Fellow Olle Järv, olle.jarv(at)helsinki.fi.

Reflections on the 8th Nordic-Baltic Migration Conference

The second panel ”New Challenges in Cross-Border Mobility, Nordic-Baltic Region” in the Nordic-Baltic Migration Conference in Tallinn, Estonia

Olle Järv from the Digital Geography Lab attended as an expert panellist in the Nordic-Baltic Migration Conference “Cross-border Mobility in the Nordic-Baltic Region organized by the Nordic Council of Ministers’ Office in Tallinn, Estonia on September 18, 2020. Olle participated in the second panel ”New Challenges in Cross-Border Mobility, Nordic-Baltic Region” together with Uffe Palludan (Palludan Fremtidsforskning), Jonas Wendel (Nordic Council of Ministers’), Rolle Alho (Uni Helsinki), and Saara Pellander as a moderator (Migration Institute of Finland). In the panel, Olle briefly introduced his BORDERSPACE research project on cross-border mobility and transnational people, and how these research topics benefit from novel data sources such as social media and mobile phone data.

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Can we use Twitter data to estimate population distribution in Finland?

One of the main data processing steps before making use of novel data sources (e.g. Twitter data) for better understanding social processes and phenomena is the detection of users’ origins – be it at country, municipality or neighborhood level. This allows us to know whose Tweets in some geographical area (say, in a certain city or a neighborhood) we investigate. The most basic way is to distinguish locals from non-locals when examining mobility and activity locations of people. A more advanced analysis would require knowledge about origin countries in tourism studies and origin neighborhoods in segregation studies, for example.

This data processing step is also a prerequisite for cross-border mobility research – we need to know origins of people in order to categorize and analyze movements across country borders extracted from geotagged Tweets. Hence, it is the priority for our cross-border project. See, for example, the recent recent cross-border mobility analysis in the case of the Greater Region of Luxembourg from the MSc thesis by Samuli Massinen.

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Geotagged Twitter Data to Reveal Cross-Border Mobility of People

Overview of Samuli Massinen’s MSc thesis:

How can Big Data sources, such as georeferenced social media, be used in cross-border research? What kind of cross-border mobility patterns can be detected geographically over time? How can daily cross-border movements be separated from other movements? These were the main questions I was trying to find answers for in my Master’s thesis “Modeling Cross-Border Mobility Using Geotagged Twitter in the Greater Region of Luxembourg”.

The Greater Region of Luxembourg is the largest cross-border labor market in the European Union with the greatest number of cross-border workers in the area. European integration, the Schengen Area, and socio-economical divergences between neighboring countries have been the main factors facilitating human cross-border movements in the region and thus the emergence and expansion of the borderland community. Despite the freedom of movement, country borders still exist as well as their socio-economic differences. We witness the growing trend of people migrating to the other side of the country border while still working in Luxembourg. This actuates daily cross-border mobilities, which are not well known, to date. Thus, there is a distinct need to understand cross-border mobility dynamics in the region, especially border crossings on a daily basis.

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