Zishuai Tang is a data journalist from the Beijing News. He is an alumnus of USCET’s data journalism workshop.

Q: How did you become interested in data journalism?

A: I first became interested in data journalism in 2014 when I read a book called the Data Journalism Handbook. That was the first time I heard about data journalism and started to learn about it. After that, when I was in university, my professor’s field of study was the relationship between text-based journalism and quantification. This caught my eye, and I began to pay more attention to data journalism.

Q: What are some of the challenges that you face when working in data journalism? How do you cope with them?

A: In my experience, I’m usually covering very interesting issues, but the relevant data is hard to find. I think this is the biggest challenge in data journalism. Because my department pays attention to people’s daily lives, the news topics are relevant to those topics. However, unlike economic and business news, the data on these topics is not so comprehensive. Our solution is that we manage all the data by ourselves, use complementary datasets, or search for the data internally. But if the data is not enough, we have to move on. 

Q: Could you share with us an article that you are proud of? What happened during your writing that makes you feel this way? What difficulties did you face?

A: I wrote an article in early July called Every Summer Children Get Trapped in Cars and Die, Especially on School Buses. That June, I read two reports about it and learned that such incidents happen every year. So, I decided to write a report about it as well. However, when I tried to look for the data about these incidents, I found that the authorities did not have the statistics. As a result, I could only search for such data on the Internet and try to figure it out. My team and I dug through Chinese media and found more than 140 news articles on the topic. I think the data filtering was the most difficult part. Our team collected and sifted through articles for more than a week before we got all the data we needed. In the end, I found something in the data that people had missed—namely, that the highest mortality rate is for children trapped in school buses. This kind of life-and-death report hits close to home, and is important for our society. I hope this report will have a positive impact on parents.

http://www.bjnews.com.cn/graphic/2018/07/09/494359.html

Q: What is your view on data journalism as a news reporter?

A: When data and journalism are combined, it is more objective. In the past, news was all about text. I also think subjective points of view were stronger, and the journalist’s logic would be implicitly reflected in their writing. However, when the data is mixed in, the news is more objective. The story is explicitly backed up by data, which makes it look less subjective.

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汤子帅是新京报全媒体部的数据新闻编辑，也是数据新闻工作坊的校友之一。

Q:你是怎么了解到数据新闻的？兴趣使然还是工作需要？

我在2014年的时候看了一本名叫《数据新闻手册》（Data Journalism Handbook）的书，这是我最早开始接触到数据新闻并开始了解。之后，我在大学里的导师主要教授的课程是关于量化传播，所以我也潜移默化的开始学习数据新闻。

Q:运用数据新闻是遇到过障碍吗？都有什么样的障碍以及如何克服它的？

在我的工作经验里，可能经常会遇到选题非常有意思，但是数据并不好找到，这是我认为数据新闻报道里比较大的障碍。因为我工作的部门关注的是民生新闻，选题都比较生活化，所以可找到的数据并不完全，不像经济或商业方面数据偏多。所以我们一般的解决方案是自己整理数据、用替代性的数据解决、或者寻找报社内部渠道寻找数据。如果实在是数据太少，就只能够放弃了。

Q: 可以分享给我们一篇你感到自豪的文章吗？我们想知道写这篇文章的过程中发生的故事——为什么你对这篇文章感到自豪？在写文章的过程中有遇到什么困难吗？

我在七月初的时候写过一篇报道，名叫《每年夏季都有孩子被困车中死亡 校车是“重灾区”》。我选择这个题目是因为我发现六月的时候就有两篇关于小孩被困在车中遇险的报道，我自己印象中也发现此类事件每年都会发生，就想要做一个这样的报道。但是当我想要去找寻数据时，发现官方并没有这方面的数据统计，所以只能够自己去网上搜索，然后整理下来。我和团队在国内报道过类似新闻的媒体中进行筛选，最后整理出140多条新闻。数据筛选是最困难的，我们团队一起一共筛选了一个多星期才整理完全部的数据。最后根据整理出来的数据，我们发现小孩困在校车里，死亡率是最高的。这类的新闻报道贴近生活、贴近生命，具有很强的社会意义。我也通过数据发现了平时大家关注不到的东西，比如发现了困在校车里的小孩死亡率最高。我希望这篇报道能够在儿童监护上，对父母有启示作用。

http://www.bjnews.com.cn/graphic/2018/07/09/494359.html

Q: 作为一位文字记者，能谈一谈你对在工作中结合数据新闻的看法吗？

我觉得当新闻与数据结合在一起的时候，会显得更加客观。以前的传统新闻都是纯文字，我觉得主观导向性会更强一些，记者的潜在逻辑都会反映在报道中。但是当数据融合在里面的时候，提供的报道会更加客观。报道里陈述的事情有数据作为支持，主观性没有这么强。