This project is an interactive data story on the development of China – the most populous country and its Five-Year Plans over the years and its extensive impact on China’s social development. With the use of intelligent textual analysis and interactive technology, the project analyzed and visualized eight Five-Year Plan documents – more than 360,000 words in total – which have been archived since 1953.
The project guided the readers through China’s development over the years in light of the five-year plans. The uniqueness of content and presentation format attracted 968 mainstream media to repost this presentation over social media, including The Associated Press, Yahoo Finance, Canadian Business Weekly, and the Associated Press of Australia, potentially reaching 240 million people across the globe. It was reposted in English, Spanish, French, German, Japanese, Indonesian, Russian, Korean and other 17 languages.
In terms of narrative, the product adopts Martini’s data news visualization framework, which is rare in regular news reporting but is more common in the field of data journalism. This narrative provides readers with a cover page and a linear frame that can be interrupted to trigger event response by sliding.
We used Jquery, html, css languages to compress text and combined the P5.js visual programming language library to query the keywords in the text, creating a visual line of the keywords in the text. In terms of dissemination, the work is bilingual, Chinese and English, adapted for both PC and smartphone/pad, making it efficient to share on social media.
What was the hardest part of this project?
The most difficult part was finding the “story” in these complex policy texts. And we tried to tell this story from two approaches. The first was to combine decades of textual changes, including text order, word frequency, new phrases, etc., with actual changes in socioeconomic conditions to determine how the relevant five-year plan actually affected the relevant Chinese sectors. For example, we tried to find out if urban-rural income ratio actually decreased or not after the FYP called for “narrowing the social gap.”
The second challenge was how to effectively deliver a large amount of information to readers. With a lot of data from several decades, it was a daunting task to lead readers to “travel sixty-five years” and feel the changes without feeling too much pressure.
To solve these issues, we adopted the Martini Cup method to guide readers to a general understanding of the five-year plan, and then provided them with choices to explore at will.
What can others learn from this project?
This project offers great insights into handling textual data analysis and visualization. Chinese text is not like English text – combining the same characters in different ways can express totally different meanings. Thus, it is sometimes impossible to use computer languages such as Python to analyze the Chinese text. We spent a lot of time dealing with the text by hand-picking the important phrases. The second part was how to visualize these data. So, we put all the text of each five-year plan on a page and differentiated it by using different font sizes. Meanwhile, we collected some other data to support and show how policies influence aspects of the Chinese society.