Its my first ever blog post on my first ever blog and this post is all about the first class of my first ever data visualization course in NUS. Talk about a whole lot of firsts! While first attempts can be extremely daunting, they are also exciting, enriching and enjoyable. Which is why I am super excited about this blog and my data visual visualization class. Hopefully, by the end of the course, my blogging and data visualization skills will have improved by leaps and bounds.
As a student, I inevitably use infographics , pie charts , bar graphs etc to represent useful data in project reports. But the visuals I create are extremely simple and quite amateur like. There are so many incredibly talented people in the world who represent data in such creative ways. The visuals they create are imaginative, elegant and most importantly extremely understandable. This course should definitely help me enhance my data visualization skills. Perhaps by the end of the course, my handy work will no longer be considered amateurish.
The first class of the course saw us discussing terms such as data, visualization and infographics. The highlight of the class for me was the TED talk we watched on a father trying to understand his son’s speech patterns. The most fascinating part of this talk were the different ways data was visualized and represented. Trails to depict household activities and graphs to indicate where certain words were used most often were used to represent and understand how a 2 year old boy learned to speak English. The video was an insight into how huge volumes of data should be analyzed, categorized and represented in an understandable format.
Check the video out at: The birth of a word
Our first ever class assignment was to examine the Singapore 2011 general elections tracker and try to infer useful information from it, a seemingly trivial task but complex nonetheless as the tracker was rather difficult to comprehend initially.
Here is what I inferred from the tracker:
1. The tracker represents the most popular terms or terms searched for most often by the Singapore public in the days leading up to the general election 2011.
2. Popularity of a term over time is depicted using color coded graphs.
3. Relationships between popular terms and related articles and tweets is depicted using color coded graphs.
There were many elements of the tracker that I was impressed with and a few elements that I did not like.
1. I was impressed by the graphs used to depict trends in popularity
For example, in the image above, it is evident that the term PAP is very popular and has remained popular over the timeline of 5th May to 8th May. The usage of graphs made it very intuitive to understand how the popularity of a term had changed over time.
2. Headings such as ‘Running’ , ‘Key Terms’, ‘Latest’ gave a clear picture on the latest and most recent terms.
3. Relationships between terms and related articles or tweets were very well defined.
4. The interactive user interface made it easy to click on a term and view its popularity + related tweets and articles.
For example, the image above very clearly shows the change in popularity of the word ‘video’ on the left hand side and also depicts articles and tweets with the word ‘video’ on the right hand side.
5. The tracker represents a large amount of data with minimum graphics. It does not add any unnecessary elements just to look attractive.
1. The numbers put next to the key terms are not easily understandable.
For example, in the image above, the use of the numbers 11 , 2 , 10, 3 is not easily understandable. Only after a little exploration of the visualization, it becomes evident that the numbers depict changes in popularity over time. For example, on 7th May, WP was the 11th most popular term but it improved to the 2nd most popular word on 8th May.
2. While the tracker claims to fairly depict the most shared content on social media, Twitter appears to be the only source that is well represented. If Twitter is the only social media source utilized, the tracker may not be a very fair representation of the truth.
3. The colors used for the graphs are misleading. It is not very evident as to what is the purpose of the color codes used for various graphs.
My suggestions for improvement:
1. An easier color coding on the graphs. For example, green to indicate increase in popularity and red to indicate drop in popularity of a term.
2. More social media sources such as Facebook, Quora, Pinterest and Google+ for the data used in the visualization.
3. Use of a horizontal bar graphs to more clearly indicate the popularity of a term or how many times the term has been shared or been searched for.
If you would like to check out the tracker, the link is: Singapore General Elections 2011
On the whole, the first class of data visualization was interesting and I am excited about what is in store for the rest of the semester!