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09 02 2018
Karin van Es: Data-driven approaches are often particularly good at raising new questions, which may need to be answered with different methods
On data-driven research and visualization with Karin van Es from Utrecht Data School, who gave a lecture at Data (for) culture conference in Katowice
Łukasz Mirocha, Karin van Es
18 10 2017
12 things you will learn about Katowice culture thanks to Medialab research
Only a few years ago, no one would have conceived a thought of Katowice becoming a city associated with culture. In 2015, however, following a brief yet intensive period of investment in cultural infrastructure and cultural events, Katowice joined the exclusive international group of UNESCO Creative Cities. Has the city undergone a true cultural revolution? Is Katowice’s current en-vogue status just a passing fad or could it be a herald of major changes in the city centre? In order to find out, we teamed up with cultural researchers, designers, programmers and analysts to study responses given by 3633 participants in over a dozen local events, and analyse tens of thousands of posts published in social media and web-based information services. What we present below is a 12-point list of things to look out for in the exhibition and report summarising our project.
Karol Piekarski
20 08 2017
Researching Facebook and researching with Facebook. The story behind the app to verify the declared participation in cultural events
We present a step-by-step account of the design and implementation of a Facebook application that will allow us to study the participants of cultural events promoted as part of Poland’s most popular social networking site.
Hanna Kostrzewska
15 05 2017
Address mapping: how we process spatial data from a survey
With a host of easy-to-use online tools available, spatial data visualisation has become a helpful research tool. Having accurate data, we can conveniently generate clear and engaging statistical maps. The situation becomes more complicated when we work with faulty or erratic content downloaded from social media or received from survey participants. To get any use out of it, the data needs to undergo a laborious verification process.
Karol Piekarski, Paweł Jaworski
25 04 2017
Visualisation of Facebook data. What you will not learn about your fan page from admin stats. Part 2.
We typically expect the analyses of large data sets to provide us with simple clues that will increase the number and engagement of visitors to our page. Detailed research on interactions with Facebook posts shows that trends tend to vary from month to month, making it difficult to find universal rules governing social media. Our visualisations, therefore, do not provide ready-made solutions, but rather help users embark on data exploration for a broader look at fan page statistics.
Karol Piekarski, Waldemar Węgrzyn
21 03 2017
Where’s the Culture? A Cultural Event Geography by Facebook
Is it possible to map cultural activity across the city based on social data? Well, we gave it a go! Using the information available on Facebook, we set out to trace the dynamics of the local cultural life to find out whether the city’s geographical centre is also where its cultural heart beats.
Hanna Kostrzewska, Paweł Jaworski
09 03 2017
Visualisation of Facebook data. What you will not learn about your fan page from admin insights
Administrators of Facebook pages have at their disposal a set of advanced statistical tools to track and study the engagement of its users. However, if they want to compare their own performance in relation to similar institutions or competitors, they are forced to seek the paid services of analyst firms. Alternatively, they may refer to the data from another source, i.e. Facebook’s API. This is exactly the way we decided to check whether researchers or cultural event organisers can gain a basic understanding of any fan page, while performing their own studies and visualisations.
Karol Piekarski, Waldemar Węgrzyn
10 01 2017
What does data tell us about culture? Data-driven research
Thanks to data-driven research we are able to explore the relationship between knowledge about the behaviours of social media users with the research on consumers of culture conducted by traditional methods. This way, we combine the accuracy of surveys and their capacity for revealing the motivations of respondents with the advantages of automated analysis of large data sets, which makes it easy to discover the so-far unnoticed trends and relationships.
Karol Piekarski