The meaningful and meaningless data in data visualization projects.
This week, I had a look at the data visualization project, named visual earth, which is a research study in Cultural Analytics Lab. This project uses the big dataset collected from Twitter, and the author made a connection between image sharing and economic development. In this project, they did a deep analysis of how the number of images sharing on twitter related to economic developments in different areas around the world. In the end, they also make a prediction between developing areas and developed areas.
(picture from http://visual-earth.net/)
They make a good visual graphic that can reflect the information directly. I can clearly find how different areas different from each other. For example, the size of the blue area in Europe and North America where citizens have high income is significantly bigger than the rest parts of the world. However, the area of China from which I came only covered by a small size of blue color. If the authors only collect the images from Twitter, I start to doubt that if they consider the situation in China. To be specific, because of the network policies, Chinese people are hard to get access to social software which are popular in western society, such as Facebook, Twitter, and Instagram. Furthermore, Chinese people have their own social software, such as Wechat, Sina Weibo, and so on. For this reason, I do not agree that the number of images sharing on Twitter in different parts of the world can be used to reflect the economic development in different areas around the world, even though they mentioned the ‘Geographic Differences’.
(picture from http://visual-earth.net/)
The data analysis they used in this project, in my mind, is too specific to prove the information they want to show audiences. From this project, I was thinking about how an artist can make strong connections between the data they chose and the information they want to show and if we can distinguish them as meaningful data and meaningless data.
Ref:
http://visual-earth.net/