Well hello there stranger!
Welcome to the emotional Weekly Rollercoaster Dutch people experience every week! Why do Mondays suck? Why do we thank God it's Friday? And why are we all lazy on Sundays? By combining data from Google Trends, Last.FM and factual data from Spot.nl we attempt to explore and define our mood for each separate day. Do we really feel depressed on Mondays as opposed to the happiness we experience on Fridays – as the universal clichés makes us believe – and what are the dominating factors which influence this change in mood? How much time do we spent on different activities such as grocery shopping, watching TV, exercising, and other activities on different weekdays? In other words; how do we experience the Weekly Rollercoaster we find ourselves in?
As this visualization is completely interactive, please do not hesitate playing around and exploring by toggling certain datasets on and off. Want to know more? You can find a more elaborate explanation on our About page.
Hi, stranger. You've clicked on the About page so let's take a minute to talk about the 'About' of this website. Every year 'Show me the Data' is an international multidisciplinary course and event. We, the students of this subject, combined our Artificial Intelligence, New Media and Design superpowers and created this Data Visualization for the 'Show me the Data' event (28 March 2013) over a period of just 8 weeks.
But why this Weekly Rollercoaster? We've got several reasons why we thought of and picked this project to work on. Firstly, we all love the grumpy memes about Mondays. Even though we are all from different backgrounds we all get them and this is a sign in favor of the universal clichés about the weekdays, such as: "Oh no, it's Monday again", "Thank God it's Friday" and "Lazy Sunday". If we may believe these clichés we all experience an emotional rollercoaster each week. So we wanted to do something with this quite vague starting point. Are they kind of true? Do we all feel depressed on Mondays and do we all celebrate Fridays? But also: Why? What factors influence the story and experience of each separate day? We were and are fully aware of the fact the science of Artificial Intelligence has not yet reached the point of being able to scrape and interpret mood data fully automated and without errors. This given fact didn't stop us, but on the contrary, made it even more interesting to dive in this underdeveloped field and experiment with it.
But how? When we looked at the possible approaches towards our topic, we let us get inspired by Google Flu Trends. Google Flu Trends proved how a search query is not just a search query and nothing more, but it really says something about the person behind the desktop searching for it. This project used flu-related search queries and geolocation to map out flu real-time and additionally predict flu. We wanted to know if this approach is also applicable for mood-related search. So, for our project we used Google Trends and looked for depression-related search queries in The Netherlands to be able to map out the experience of each day by Dutch people. Do we really feel more depressed on Mondays, like the clich&eavute; lets us believe? Just as Google Trends interprets flu rates higher when the searches for flu-related queries are higher, we interpret the level of happiness lower when the searches for depression-related queries are higher. The Google Trends data the Weekly Rollercoaster uses to visualize the weekly mood of Dutch people is dynamic and refreshes every day. Because it refreshes every day the line visualizes the general mood over the last 90 days until now.
Now we can see the emotional rollercoaster of the week, but what factors influence this? Because music is something that influences our mood, but is also something we listen to according our mood, we used the Last.fm API and Echonest to see how music affects it, but also whether we listen to depressing music more on Monday than on Friday. Music factors that we've included are: Beats per minute, danceability, loudness, energy and number of plays. This data is an average of two random weeks, it shows the interesting story of people listening to happy music when they’re feeling down and the other way around. In the future we would like to make this data just as dynamic as the Google Trends data.
Lastly, we included a third dataset and this one exists of factual static data from SPOT. This data is about how Dutch people spend their time (in minutes) each day. This allows us to see why the story and experience of each day differs and which factors influence our mood positively and negatively. The visualization works with percentages. The minutes spend on the 15 factors for each day are added up to a 100% and the stacked bars thus show what the time spend in percentages of one factor is in comparison with the other 14 factors of that specific day.
Because we are all raised in the 2.0 internet world, we'd love to hear from you! Want to chat, want to contact us or want to give us some feedback, please use this form below to send us your thoughts and we'll get back to you.Close
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