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Survival-Guide-Of-Data-Journalist

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Background and motivation

Nowadays, we see more and more words with #data journalism# appearing on the internet, social media platforms, television and newspapers. In the era of the revolution and innovation of internet technology, data has different interpretations for different people. Now, the news industry no longer relies on the news of the past to inform the public after the production of printing machines, but has been recorded and disseminated when news are happening. It is also because of this, news is screened in the wave of the internet and is often overwhelmed by opinions.

Therefore, in the media industry, data journalism has become the hottest and most important category at present. Data journalists have also become a popular choice, changing more and more journalists or those who want to become journalists in this direction.

As students of communication program, who also take part in data courses, so we hope to investigate and find what are key trends and skills to be a data journalist. In this way, we can contribute some information or reference for those potential students who are willing to be a data journalist in the future.

Executive summary

We hope to provide data journalists with a "survival guide" through crawling data so that more people can understand the relevant background and skills of data journalists. We mainly crawled the corresponding data from the data news websites and related jobs websites, and then further expanded the links to the Github and Twitter accounts of the current data journalists to analyze their usage.

At the same time, we used those data combining with the existing data news education materials vertically and horizontally to look for the employment status and prospects of Data Journalist. Using all kinds of libraries learned in class to analyze the crawled data and visualize our data to get the final comprehensive charts, and make a summary of our data.

Quick pointers to key files

Key jupyter notebook files

1.The DJ-contribution-tendency-area.ipynb contain the contribution tendency analysis of DJ.

2.The Analysis-in-US.ipynb includes contribution analysis and Twitter & job description text process

3.The directiory-distribution.ipynb includes all maps. (nbviewer)

Others

1.Csv: the original csv includes all DJ information

2.Images: all visualization results of our research

3.Prezi: DJ gogogo

4.Final report: without code

5.Bonus:The Survival Guide Of Data Journalist (GitHub Repo)

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