Digital urban spaces of Helsinki seen from Instagram data have high language diversity, the topics of Finnish and English posts differ spatiotemporally and content-wise to some extent and more is discovered in my Master’s thesis. Finnish and English language posts dominate different areas of Helsinki and topics of Finnish posts have connections to everyday life while English topics are influenced by tourists
With ubiquitous internet access and increasing amounts of social media users and content, an ever larger part of social interactions and common discussions are being augmented with digital means of communication. This renders social media data valuable for scientific inquiry in order to understand contemporary societies, cultures, and phenomena. Social media data is being produced constantly in vast quantities and is mostly produced by users living in urban areas. The data produced in social media can have a reference to a real-world location e.g. in the form of a geotag or geographic coordinates enabling spatiotemporal analysis. In order for scientific knowledge to keep up with the quick changes in society and cultures enabled by the internet and social media, social media data sets need to be investigated and doing this requires powerful novel and interdisciplinary methods.
In my thesis, I delved into the digital urban space of Helsinki by applying topic modeling to Finnish and English Instagram posts’ captions from Helsinki. By looking at the topics of Instagram posts made in both English and Finnish languages, my aim was to discover how language affects Instagram topics, the spatiotemporal distributions of these topics and whether linguistic technologies are applicable in geographic research. In order to do all of this, a number of preprocessing steps were required. The language of the posts had to be identified in order to separate Finnish and English posts from another. After this, the caption texts were lemmatized to make LDA topic modeling viable. Lemmatization is a natural language processing technique with which inflected words are returned to their basic ‘dictionary’ form. For topic modeling of morphologically rich languages, such as Finnish, this is a critically important step without which LDA topic modeling would not yield sensible results, but it is recommended for English as well. Then the lemmatized captions were vectorized and fed into an LDA topic model which modeled language-specific topics for the Helsinki area and a few city districts.
Plotting the hourly Instagram posting activity by each weekday reveals that Instagram posting frequency in Helsinki follows a three-peak rhythmic structure: peaking at common meal times each day of the week. The temporal structure also shows that Saturdays and Sundays are the most popular days to post on Instagram in Helsinki. These findings hint at a connection between Instagram posting in Helsinki and leisure time activities quite strongly, suggesting Instagram data might be suitable to find out where Instagram users are and what they’re doing on their own time.
To decipher which topics are popular in Finnish and English Instagram posts, the language of the posts was identified revealing the diverse linguistic landscape of Instagram posts in Helsinki. By only focusing on Finnish and English, a lot of knowledge is lost in my analysis, underscoring the importance of a multilingual approach in future work. The geolinguistic division between Finnish and English Instagram posts in Helsinki shows a few key patterns. Firstly, the city center is the area of highest posting intensity, but smaller posting hubs appear along with major transport nodes in Helsinki. Secondly and perhaps more interestingly, central Helsinki is quite clearly divided in two between the languages. Finnish is more popular in areas north of Hakaniemi, while English comes out on top in the southern parts of the center. The main dividing line seems to be Töölönlahti and the small channel connecting Töölönlahti to the Baltic sea, which has historically been the dividing line between the working class in the north and the bourgeoisie in the south. The biggest relative differences between the languages are in peripheral areas with very low post counts suggesting that popular areas for posting are popular for both languages.
Finnish and English Instagram posts’ topics differ both spatially and temporally at different scales, even though Instagram data was shown to be similar in content and temporal rhythm between the languages. Posts in both languages mostly deal with leisure-related topics, but Finnish topics have several references to everyday life, while English topics do not. Also, Finnish posts didn’t have one numerically dominant topic while as English posts did: ‘morning’. The spatial structure of the topics reflects the complexity of social media content, generality of the topics and the fact that posting location might not specifically relate to the topic of the post. Also, Instagram’s geotagging is based on points-of-interest which introduces slight to moderate spatial inaccuracy into the data as the exact posting coordinates are not recorded. There is, however, some spatial logic to the topics, for instance, the prevalent topic of Suomenlinna island is ‘summer’ for Finnish posts and ‘New Year’ for English posts, topics around the Olympic stadium revolve around sports. Statistically validating the connection between the topic and the underlying geographic region is highly problematic if the topic is very general.
The topics become more specific at city district level which is to be expected with the limited spatial extent of a city district. However, at the city district level, the POI-based location structure becomes more problematic due to the aggregation of posts under POIs. At the city district scale, English topics have clearer references to touristic sights in the city districts suggesting a presence of tourists or at least sightseeing as an activity in the data set. Finnish topics, however, maintain a connection to everyday life with topics like “work”, “family” and “everyday life” and touristic sights are not mentioned.
There are a few things to consider when doing research with social media data. First, social media posts are often about subjects the user considers positive creating a positivity bias into the data. Second, results from social media analyses only represent the users of its particular social media platform and finding out to what extent this group represents the population as a whole is difficult. Third, the locational accuracy of posts isn’t in all cases very good, because geo-tagging functionality can be based on fixed points-of-interest and not to the actual coordinates of the user at the time of posting. This means that large amounts of posts can be and are aggregated on to commonly named points-of-interest. For instance, “Helsinki, Finland” was one of the most popular location names in the data and surprisingly consisted of numerous different points across Helsinki. Fourth, social media posts are multilingual and most of the tools for content analysis have been developed for English and most of social media research deal with English content. Including minor languages into the analysis would ensure a broader and less biased understanding of what is going on in social media. Fifth, social media companies are constantly developing and changing their APIs making access to data and reproducibility depend on the whims of social media corporations. Regardless of these error elements and limitations, social media data can be a very fruitful data set for scientific analyses of the city and (some of) its people.
Here’s the link to my Master’s Thesis (only in Finnish)
The users of the popular local bike-sharing system in Helsinki are mainly young adults and living in the downtown shows my recently finished master’s thesis. Almost 80 % of the trips were made by the users who were living in a postal area with at least one bike station in 2017, which shows how the service has been embraced especially by those living in the central ares of Helsinki.
The new bike-sharing season is here again and the system coverage are has expanded In Helsinki! Bike-sharing systems have become popular and attracted wide interest in Finland and elsewhere in recent years. Many cities have employed shared bikes, which aim to provide new mobility option for citizens. Shared bikes are also strongly linking to targets to increase the share of sustainable travel modes in cities, which partly explains their enthusiastic reception by many.
My master’s thesis titled as ”Bike sharing as part of urban mobility in Helsinki – A user perspective”, which examined bike-sharing users is now accepted and published. The work, accepted with the highest grade, focused on bike-sharing users, usage patterns and how equally the system is serving the citizens. The aim of the work was to bring new information to support planning and development of the bike-sharing systems in Helsinki and elsewhere. I used a data set provided by Helsinki Region Transport and City Bike Finland, which contained all the bike-sharing trips (~1.5 million) from 2017. Before the data analysis, I had systematically reviewed almost 800 scientific articles focusing on bike sharing.
Internationally, bike-sharing system have been hugely popular and in the public discussion, the systems are often covered positively. Meanwhile, there has been critique in the scientific literature that shared bikes would only be serving certain population groups. This contradiction got me interested in to examine the local users in Helsinki more closely.
The study showed that in Helsinki, the use of bike-sharing system has been internationally high. Young adults are emphasized in the user base and especially when comparing by the number of trips, male users are over represented. Compared to regular cycling, the profile of bike-sharing users is less diverse than among all cyclists in Helsinki. Most of use is generated by those, who have a bike-sharing station in their neighborhood. The usage patterns of these users are also different compared to those who are living outside the station coverage area. For example, the users living outside the area have significantly higher shares of potential public transport integrated trips on average. Use activity and the subscription type were also found to be important factors shaping usage patterns.
The study also showed that bike-sharing systems have been actively and extensively studied. However, the study areas seemed to be concentrated to cities where bike-sharing data were available. This observation highlights the role and the need for open data in studying new mobility modes.
The upcoming summer will be interesting from my results’ perspective now when the bike-sharing system area in Helsinki expands. It remains to be seen whether the over-represented user groups were only more eager to quickly embrace the new system in 2017 or whether the same usage patterns still prevail after the expansion. From the equity perspective, the bike-sharing system will be now available to a larger group of citizens better than before. Young adults have found the system well, but it is important to pay attention that shared bikes and cycling are being promoted among the whole population to better advance and increase their role as part of sustainable urban mobility.
The full work can be found from here: MasterThesis_EliasWillberg
Animated visualization of the system dynamics can be found from here https://blogs.helsinki.fi/accessibility/2018/05/18/one-day-of-city-bikes-in-helsinki/
The abstract selection for the NECTAR conference 2019 is now done! We received a record number of abstracts, 190, which was fantastic!
The conference, which will be organized by us and the University of Helsinki together with the Aalto University, Helsinki Institute for Sustainability Science (HELSUS), Urbaria, and the City of Helsinki takes place 5-7th June in Helsinki.
Registration links to the accepted participants have been sent via email!
There was a great deal of high-quality abstracts and the selection process was certainly not easy. The selection was done based the scope of the abstract, scientific quality, NECTAR membership and the possibility to fit the presentation in a coherent conference session. The sheer number of papers challenged us, but as the picture shows by sticking with the good old pen and paper style we were able to handle the task!
Looking forward to a great conference!
Call for papers for NECTAR 2019 conference is now open!
Digital Geography Lab and University of Helsinki will organize an international NECTAR conference (5.-7. June 2019) in Helsinki together with the Aalto University, Urbaria and the City of Helsinki. NECTAR is a scientific research network concerned with transport and communication issues and the biannual conference brings together transport and mobility experts all over Europe and elsewhere.
We have two fantastic key note speakers in the conference, professors Jan Gehl from Denmark and Tim Schwanen from Oxford, UK.
The call for papers for the NECTAR 2019 conference has now opened, and closes on 21.1.2019.
The theme of the conference is “Towards Human Scale Cities – Open and Happy”. The conference calls for presentations on advancements in the field of transport, communication and mobility. The focus of the conference will be on urban transportation and the new possibilities that open data and digital technologies provide for mobility solutions. For example, presentations may discuss how transport policies are and should be changing, present emerging ways of organizing the daily mobility to make cities more sustainable and more pleasant or present novel ways of analyzing transportation and mobility from the perspective of people.
Welcome to “open and happy” Helsinki!*
*See more information and submit your abstract in the conference website: https://www.helsinki.fi/en/conferences/towards-human-scale-cities-open-and-happy
Understanding where people are and when – What is the pulse of the city? – is of high importance in urban planning, management and governance. Accurate information of the dynamic population distribution is crucial for example for land use and transport planning, disaster and conflict preparedness, evacuation purposes and for mitigating the spreading of diseases.
So far, our understanding of the whereabouts of people in time and space is scarce and predominantly based on static census data – people are expected to stay at home, although people rarely stay there the entire day. For instance, in (place-based) spatial accessibility research the use of home locations are considered as a proxy for origins of people despite the widely acknowledged criticism of the approach.
Fortunately, novel temporally sensitive spatial data sources, such as mobile phones, geotagged social media posts and smart cards can provide new solutions to uncovering the actual whereabouts of population in space and time.
In my thesis, I set out to uncover the spatio-temporal population dynamics in the Finnish Capital Region using mobile phone data. The data was provided by one of the main mobile network operators in Finland. Network-driven mobile phone data was interpolated to statistical 250 m x 250 m grid squares to estimate the hourly population distribution on a typical weekday (Monday-Thursday).
To refine the estimated population distribution derived from mobile phone data, I applied and adapted an advanced interpolation method developed by the Digital Geography Lab that uses ancillary information of land use, floor area and use type of buildings, and a time use survey to improve the accuracy of the results. The results were then validated against official census data during night-time (2 AM – 5 AM), which showed that the advanced interpolation method significantly improves the population distribution derived from mobile phone data.
The results highlight, that network-driven mobile phone data can be used to catch the daily pulse of the Finnish Capital Region. The morning hours show a clear transition in the whereabouts of people from residential areas to work place areas. The afternoon pattern is however not as straightforward – people may stop by a store or undertake leisurely activities on their way back home. As a matter of fact, population concentrations in the shopping malls and recreational areas are highest in the evening according to the results. Also, the polycentricity of the study area as well as the incoming and outgoing population flows along the major roads in the morning and afternoon can be distinguished from the data.
The typical home-work-home rhythm can clearly be seen for instance in the Aalto University campus area in Otaniemi. During day time, the concentration of population is highest in the campus area, but as the evening draws closer, the concentration shifts to the Teekkarikylä residential area at the end of the cape.
So, what’s next? I will implement the dynamic population distribution to examine the 24-h accessibility to grocery stores and introduce the first fully dynamic accessibility model in the study area using an approach developed by the Digital Geography Lab. Stay tuned!
Geoinformatics MSc. Student
Digital Geography Lab organizes a session at the Annual Meeting of Finnish Geographers 2018: Cross-Border Dialogues & Finland: Human Mobilities, Social Interactions & Transnationalism.
Send your abstract to our session by September 23 or just come to see interesting presentations!
Session chairs: Olle Järv, Kerli Müürisepp & Tuuli Toivonen (Digital Geography Lab, University of Helsinki)
In the EU “borderless world”, cross-border interactions and integration are regarded as key drivers towards socially and economically more cohesive territorial development and well-functioning societies. Increasing human mobilities and socio-spatial interactions transcending state borders have a role in forming many societal phenomena such as new functional cross-border regions, transnational people and transnationalism, at large. These developments have further implications on societies in relation to integration processes, identity formation, social (in)equalities, governmentality, planning and security, among many others.
Cross-border interactions between Finland and its neighbouring countries follow the overall trend. For instance, while tens of thousands of people have their daily lives already connected to both Finland and Estonia, stakeholders advance the Helsinki-Tallinn twin-city concept by planning and executing new strategic infrastructure projects to better connect the countries. As cross-border mobility flows grow, a more comprehensive understanding about complex socio-spatial practices beyond state borders and its consecutive impacts on societies is needed. In addition to conventional approaches, the application of novel (big) data sources allows to develop new theoretical concepts and methodologies to provide valuable insights for given research.
The session aims to present and discuss theoretical, methodological and empirical research on cross-border mobilities and interactions, transnationalism, and implications on societies it involves. A concentrated discussion is facilitated at the end of the session.
The topics we welcome include, but are not limited to:
- cross-border human mobility (daily, leisure, migration);
- social and spatial interactions of people from the neighbouring countries in Finland;
- transnational people and transnationalism;
- inequality and segregation;
- social engagement and integration;
- applications of novel (big) data sources and new methodologies;
- functional cross-border regions/transnational spaces;
- Estonians and Russians in Finland.
All sessions descriptions at the 2018 Meeting can be found here
Digital Geography Lab has published the 2018 version of the Helsinki Region Travel Time Matrix. The matrix contains travel times and distances between all 250 meter grid squares in the capital region of Finland, with public transportation, car, bike and walking, at different times of the day.
The previous versions of the matrix have been published in 2013 and 2015, allowing analyses of travel time changes due to big infrastructure projects in the region. Biking is included in the matrix for the first time. The data is available openly, alongside with the tools that were used to produce it.
Comparisons between different travel modes and years reveal interesting patterns in the accessibility of the Helsinki region. The most accessible grid squares have moved northwards from the city center. Still, the central area of the city is the best reachable by public transportation, while the ring roads in the outskirts of the city are well-reachable by the car-driving population. Biking is a competitive mode of transportation and beats other modes of transport in distances shorter than 5 km, a bit depending on the place and naturally the speed of the biker. The Travel Time Matrix provides biking travel times for fast and slow bikers. The speeds have been estimated based on Strava sports application, as well as city bike system of Helsinki.
The big infrastructure changes like the opening of a new metroline (Länsimetro) has had moderate impact on the accessibility of the region. The travel times have become shorter on average in Lauttasaari and Otaniemi, and longer in parts of Espoo.
Download the data from here.
- Dynamic Cities: Location-based accessibility modelling as a function of time, Applied Geography – https://www.sciencedirect.com/science/article/pii/S014362281731144X
- Power point on changes in the accessibility in the region: http://bit.do/aikamuutokset18
- Online interactive visualization and analysis tool for the data: www.mapple.fi
Click to enlarge
Creator: Elias Willberg / Digital Geography Lab
The visualization shows all the trips (n~7200) made by Helsinki bike-sharing system bikes on Monday 15.5.2017 . Because the data set does not contain GPS tracks but only the start and the destination points, the paths for each trip shown in the map are not the real ones but assumed using fastest routes . Based on the data set information however, the fastest route assumption is more or less valid especially during weekdays. White points are the city bike stations (n=140).
- The Helsinki city bike dataset for 2017 was provided by HSL and City Bike Finland to the Accessibility Research Group / Digital Geography Lab of the University of Helsinki. The dataset has not been published openly to this date.
- Background map: @OpenStreetMap Contributors @CARTO
About the visualization: The animation is done using QGIS time manager plugin.A big thank you also goes for these two excellent tutorials listed below that helped in making the animation:
- Geogiffery in a nutshell — introduction to QGIS Time Manager: Topi Tjukanov
Movement data in GIS 1-13 blog series: Anita Graser
The concept of spatial accessibility – the potential of opportunities for interaction – binds together the key physical components of urban structure: people, transport and social activity locations. Despite the dynamic nature of these components and the changing accessibility landscape in space-time, however, location-based accessibility research has been predominantly static (atemporal) in nature.
With the joint research between Digital Geography Lab in Helsinki and Mobility Lab in Tartu, Estonia, we propose a generic conceptual framework of dynamic location-based accessibility modelling. For that, we used our dasymetric model and integrated mobile phone data to spatial accessibility modelling as a proxy for dynamic population distribution. In case of food accessibility by public transport in Tallinn (Estonia), we empirically demonstrate the impact of temporal aspects in accessibility modelling.
Read more in Applied Geography: Dynamic cities: Location-based accessibility modelling as a function of time