Don’t forget your promise ! 2022 politics of candidates co-edit platform for Local mayor and Congressman election
Entry type: Single project
Publishing organisation: READr
Organisation size: Small
Publication date: 2022-11-07
Authors: Chien Hsin-chan, Lee Yu Ju, Wu Man-Ru, Li Fa-Hsien, Su Ting-Wei, Fu Dian-Yang, Chang Rong Xuan, Chang Yun Fang, Chen Bo-Wei, Liu Yi-Xin, Syu Siang-Yun
READr is not just a data newsroom, it is also a digital innovation team. The development of information news in Taiwan media is still not perfect at present. Although the READr is only a small information newsroom, we still try hard to have an indicative impact on the development of data journalism in Taiwan.
We always hope to make breakthroughs in every topic.Without the framework of traditional thinking, the team can make the report more creative and also keep the news professional by presenting stories in a true and complete way.
We developed a platform to collaborate with our readers to document the politics of election candidates. Not just for the record, but it’s also pretty much the only well-organized site for electoral politics that voters can view before the election. We first reviewed whether the political opinions of the current mayors during the election four years ago were fulfilled, as a starting point, and attracted readers to record the political opinions of this election for future supervision.
Taiwan has a large-scale election at least every two years, including the president, legislators, county mayors, etc., but in many cases, voters do not have a good way to clearly understand the political views or ideas of each candidate, and even the candidates Past experience and opinions, etc. Therefore, READr this time uses a large-scale public cooperation database to start a solution to this problem. This will have a great impact on Taiwan’s elections, because we encourage the public to seriously study the political opinions of candidates and upload them to others, and these political opinions will also become a tracking platform for the fulfillment of political opinions, so that the people can really supervise politicians, It will also have an impact on politicians.
This project is not just a webpage, but a complete website. We use PostgreSQL as the database for data storage, and Keystone.js is used for the data management system, which is a database management interface written in React.js. In addition, we also used Node.js plus React.js + Redux to complete the entire website. At the same time, Python is also used to regularly generate the data content of mass cooperation for open data use.
Context about the project:
The most difficult part of this project is the collection and persistence of data, because it will be a long-term topic, not just used in this election. Instead, READr can use these political opinion data to track the implementation status of political opinions, and it can be used directly in each future election without redevelopment. Therefore, this topic will also be a very important part of the Taiwan political figure database. Or we can say that we can monitor most of the political figures in Taiwan, not only their political opinions, but also their various records and behaviors.
What can other journalists learn from this project?
In many cases, these materials related to political opinions, policies, and even political personnel are the materials that reporters need to collect in many reports. But how to integrate the data and maximize the effect. Therefore, we try to integrate various data sources into a single database so that all data can be quickly integrated and searched. This will not only make future reports more comprehensive, but may even become an important reference for investigation and research in future reports.
In addition, although mass collaboration is not a new method, it can still be used as a part of data journalism. Although the energy and time required are usually relatively constant, it may not always be successful. But in fact, the cooperation of the masses can sometimes achieve unexpected results. When we need some large amounts of manual assistance or difficult-to-obtain information, we can think about the direction.