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Browsing by Subject "Twitter"

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  • Ehnström, Emil Mattias (2021)
    The number of people belonging to a language minority in Finland is increasing and people are becoming more and more spatially mobile. This has also led to an increase in transnationals and higher rates of cross-border mobility. With new methods involving social media big data, we can map spatial mobility patterns in new ways and deepen the understanding of how people relate to space. Differences in spatial mobility can for example give us an indication of the rate of integration into society. Some claim that a more spatially mobile life is a sign of success, but can we see differences in spatial mobility between people in Finland? The three language minorities considered in this thesis are Swedish, Russian, and Estonian. The history and culture of these groups are different as well as their status in Finnish society. Swedish speakers, with a national language status, have a different role in society, but do this well integrated minority differ from the other ones spatially? By using Twitter data and looking at the spatial mobility within Finland, we see where differences occur between language groups. To understand how strong ties the language groups have with neighbouring countries, we look at cross-border mobility to Estonia, Russia, and Sweden. The results show that there are differences in the spatial mobility of language minorities in Finland. Estonian speakers most frequently visit Estonia, while at the same time they are less mobile within Finland. The variation was large for Russian speakers, with some visiting Russia often and others almost never. Swedish speakers seem to have relatively weak ties to Sweden, compared to the other language groups and have very similar spatial mobility to the majority Finnish speaking population.
  • Moisala, Matti (2023)
    Migration, which can be characterized as a temporal or permanent movement of individuals or groups of people from one geographic location to another, is old as humanity itself. As a part of polyethnic states and as a polyethnic state itself, Ukrainians have had strong connections across the borders and migration has been an integral part of life and in present-day Europe, Ukrainians form one of the largest migrant groups around Europe. The main type of migration changed from economic migration to forced migration when the Russian Federation launched a full-scale attack on Ukraine on 24th of February 2022 which caused a massive influx of migrants to European countries. In this master’s thesis, I studied the effect of existing social networks on refugees’ destination choices, and the aim was to examine how the migration of Ukrainians to Europe after the outbreak of full-scale war is linked to the existing Ukrainian minority population in Europe and to the spatial distribution of Ukrainian social interactions with European countries. In addition to this, the aim was also to evaluate the use of novel big data sources, such as Twitter and Meta, and assess how they can provide new insights into studying migration. The first part of the analysis explored the strength of the relationship between existing Ukrainian minorities in EU countries and social connectedness. The second part of the analysis explored further the strength of the relationship over time between the number of refugees in the EU, social connectedness, and distance from Ukraine, and also the spatial distribution of Ukrainian refugees within the EU area. Third, the strength of the relationship was explored over time between social connectedness and the number of Ukrainian Twitter users in Europe. Last, Twitter data was analyzed to get insights into the Twitter use of Ukrainians and how the change in language use is connected to the refugee movement. Results show that high social connectedness values between Ukraine and other European countries are the result of an existing Ukrainian minority in countries. When analyzing the relationship between the refugee movement in 2022 and social connectedness, results suggest that the migration movement is connected to the existing social networks which can be demonstrated by the social connectedness index. The social connectedness index proves to predict quite accurately the mobility of Ukrainians. User information from Twitter data didn’t perform that well in analyses at least on the country level. However, on the regional level, the relationship between Twitter users and the social connectedness index yielded some better results with a moderate relationship in some months. Insights about overall Twitter usage also showed patterns of increased Twitter activity of Ukrainians in the EU and decreased Twitter activity in Ukraine after the invasion. However, in addition to the location of the users and overall activity, language use analyzed from Twitter data also provided insights about linguistic change from Russian to Ukrainian and the use of Ukrainian, Russian, and English in European countries. However, language use analysis didn’t provide significant support for assessing the dependencies between the number of refugees and language use. This thesis explored further the capabilities of the use of the social connectedness index in migration studies and also showed some of the weaknesses of social media-based big data in mobility-related studies.
  • Koivisto, Sonja (2021)
    Being physically active is one of the key aspects of health. Thus, equal opportunities for exercising in different places is one important factor of environmental justice and segregation prevention. Currently, there are no openly available scientific studies about actual physical activities in different parts of the Helsinki Metropolitan Area other than sports barometers. In the lack of comprehensive official data sources, user-generated data, like social media, may be used as a proxy for measuring the levels and geographical distribution of sports activities. In this thesis, I aim to assess 1) how Twitter tweets could be used as an indicator of sports activities, 2) how the sports tweets are distributed spatially and 3) which socio-economic factors can predict the number of sports tweets. For recognizing the tweets related to sports, out of 38.5 million tweets, I used Named Entity Matching with a list of sports-related keywords in Finnish, English and Estonian. Due to the spatial nature of my study, I needed tweets that contain a geotag, meaning that the tweet is attached to coordinates that indicate a location. However, only about 1% of tweets contain a geotag, and since 2019 Twitter doesn’t support precise geotagging anymore with some exceptions. Therefore, I implemented geoparsing methods to search for location names in the text and transform them to coordinates if the mentioned place was within the study area. After that, I aggregated the posts to postal code areas and used statistical and spatial methods to measure spatial autocorrelation and correlation with different socio-economic variables to examine the spatial patterns and socio-economic factors that affect the tweeting about sports. My results show that the sports tweets are concentrated mainly in the center of Helsinki, where the population is also concentrated. The distribution of the sports tweets exhibits local clusters like Tapiola, Leppävaara, Tikkurila and Pasila besides the largest cluster in the center of Helsinki. Sports-wise mapping of the tweets reveals that for example racket sport and skiing tweets are heavily concentrated around the corresponding facilities. Statistical analyses indicate that the number of tweets per inhabitant does not correlate with the education level or the amount of average income in the postal code area. The factors that predict the number of tweets per inhabitant are number of sports facilities per inhabitant, employment, and percentage of children (0-14 years old) in the postal code area. Keys to a successful study when analyzing Twitter data are geoparsing, having enough data, and a good language model to process it. Despite the promising results of this study, Twitter as indicator of physical activity should be studied more to better understand the kind of bias it inherently has before basing real-life decisions on Twitter research.
  • Aagesen, Håvard Wallin (2021)
    The Nordic region is a connected region with a long history of cooperation, shared cultures, and social and economic interactions. Cross-border cooperation and cross-border mobility has been a central aspect in the region for over half a century. Despite of shared borders and all countries being part of the Schengen Area, providing free movement, little research has been made on the extent of daily cross-border movements and little data exists on the topic. In light of the COVID-19 pandemic, human mobility and cross-border mobility has risen to the top of the political agenda, with new challenges changing cross-border mobility around the world. As an already very connected region, the Nordic region saw a sudden decrease in mobility and areas across borders were suddenly isolated from each other. The spread of the COVID-19 virus and the most important measures to counter the pandemic have been spatial in their nature. Restrictions on mobility and lockdown of regions and countries have been some of the measures set in place at varying degrees in different locations. Understanding the effects of mobility on the spread of COVID-19 and understanding how successful different measures have been is important in handling the ongoing and future pandemics. There is a lack of, particularly quantitative, research that investigates the functional aspects of cross-border mobility in the Nordic region. In addition, a lack of up-to-date, reliable data on human flows between the Nordic countries is missing. Research on the spread and effects of the COVID-19 pandemic in relation to human mobility, is rapidly increasing and being pioneered in conjunction with the developments of the pandemic. Through a lens of human mobility and activity spaces, how the cross-border regions in the Nordics reveal themselves by aggregating movements of individuals are investigated. The aim is to examine how geotagged Twitter data can be used to study cross-border mobility, as well as which functional cross-border areas can be estimated from movements of Twitter users and how these movements have been affected by the COVID-19 pandemic. Twitter data is collected and processed and reveal human mobility flows from before and after COVID-19 travel restrictions were set in place, making the data fit for a correlation analysis with available official commuter statistics. Using a kernel density estimation, estimations of the functional cross-border regions at different spatial levels are conducted, uncovering the spatial extent of functional regions and how human mobility connects regions across national borders. On this basis, movements of Twitter users in two time periods, March 2019 – February 2020 and March 2020 – February 2021, are compated with available statistics from the Nordic region. The results show that Twitter data correlates strongly with official commuter statistics for the region and are a good fit for studying cross-border mobility. Additionally, policy made cross-border regions does not completely overlap with the functional cross-border regions. Although there are many similarities between the policy made and functional cross-border regions, in a functional aspect the regions are smaller than the policy made regions and heavily condensed around large cities. The estimation of functional cross-border regions also show the effect of COVID-19 and measures taken to limit cross-border mobility. The amount of cross-border mobility is severely reduced and the composition of functional regions changes differently for different regions. In general, the spatial extent of cross-border regions reduce and gravitates towards the largest cities on either side of the border. The methods and results developed in this thesis provides an understanding of the dynamics of mobility flows in the Nordic region, and are first steps in increasing the use of novel data sources in cross-border mobility research in the Nordics. Further research into methods for expanding the data basis in the region is needed and further research should be conducted in deepening the understanding of demographic and temporal aspects of functional cross-border regions. Regional planning, tourism, and statistics are all fields that rely on recent, up-to-date data, and the methods for utilizing novel data sources shown in this thesis can mitigate some of the flaws that current data sources have. In combating the spread of the COVID-19 virus, it is of profound importance to understand mobility flows across borders, something that this thesis provides methods and insights to do.