MSc thesis on studying multi-local living in Finland using mobile phone data and electricity consumption data

Author: Iivari Laaksonen

Why is the study relevant?

Multi-local living can be defined by individuals or families having access to more than one residence in their everyday lives. It is a complex social phenomenon causing weekly and seasonal changes in population numbers as people move between regions. This means that the phenomenon is tightly connected to human mobility. In prior research, multi-locality has been mainly studied using official statistics that fail to capture the dynamic nature of people’s mobilities and dwelling. To address this in my thesis, I utilized spatially and temporally accurate big data sources − mobile phone and electricity consumption data − to capture people’s presence and mobility. More accurate information about multi-local living can be useful for local businesses and regional planning in rural areas.

How was the research done?

In my thesis, multi-local living was studied in Finland and in the county of South Savo, which has the highest proportion of second homes/free-time residences in the country. The study was done by analyzing spatiotemporal changes in people’s presence (mobile phone data from Telia Crowd Insights) and by examining how the changes relate to the number of second homes (official statistics) in different areas with correlation analyses. In addition to monthly comparisons, analyses were conducted separately for workdays and weekends to assess how people’s multi-local practices differ between weekdays. The study period of the thesis was from November 2018 to August 2019.

Mobile phone data also contains information about people’s origins (previous night location). This allowed to assess the proportions of origin counties of people visiting South Savo. Moreover, mobile phone data was used to assess the results of second home occupancy in South Savo gained from electricity consumption data which had been previously calculated in the MOPA research project.

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Two new studies on revealing cross-border mobility and border regions

One of the goals of the BORDERSPACE project at the Digital Geography Lab is to examine whether and how social media data such as geo-located Twitter data can reveal cross-border mobility of people and provide new insights for understanding border regions. We demonstrate the feasibility of using Twitter data in two different recently published studies – the first study from the Greater Region of Luxembourg and the second study from the Nordic countries.

 

Study #1: Revealing mobilities of people to understand cross-border regions: insights from Luxembourg using social media data”

Published in European Planning Studies

Authors: Olle Järv, Håvard W. Aagesen, Tuomas Väisänen & Samuli Massinen

Conceptually, our approach was to make big data small and meaningful by: 1) using a bottom-up concept of activity space (e.g. Järv et al., 2014); 2) using mobility as a tool to capture individual activity spaces; and 3) contextualizing mobility from the border perspective.

Figure 1. The conceptual framework of data collection and data enrichment using the activity space approach to reveal cross-border mobilities and its motives from an individual perspective.

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