Writer: Feng Shangyue
Editor: Yang Xuan, Zhao Xiaochun
Editor’s note:
We are witnessing the revolution of the media world.
Machine-based content distribution is gradually taking over the manual work of editors while the emerging “we media” is upending the ways in which content is made.
Such tremendous changes happened in as short as three years.
People may grow nostalgic sometimes, but more often, they realize that they must move on in order to survive in the new world. This holds true for editors, web portals and content creators alike. This article is dedicated to them all.
This is the Part 2 of a 5-Part Series.
Link to Part 1, Part 3, Part4, Part 5.
Traffic vs. value:
A story about Mr. Chen.
For the first time ever, Chen experienced a value shock when he job-hopped to a portal web from a traditional media company he had worked for four years.
Everything was data-based at his new job. News came out at 6:30 or 7:00 early in the morning, and almost at the same time, data was generated by the portal. Based on it, he placed some pieces to prominent space and removed others.
He has never felt so close to readers, and began to realize that his previous editorial experience no longer applied.
“How come the piece I put on the bottom turned out to get top clicks?” he puzzled: “I have to make immediate adjustments before marveling at today’s powerful technology.
In fact, Chen was struggling to fit in with this new environment. During his four years’ engagement in the traditional media business, he first worked as a journalist and then as an editor.
Back then, he always held on to the fundamental principle learnt from his predecessor: to cover big events, inform readers and contribute to society.
But it’s a different story here in a portal web, where he was taught to place news that involves celebrity, violence, sex scandal or lust on the front page—this screening criterion is backed by data, rather than editors’ experience which paper media rely heavily on.
At first, it was not easy for Chen to accept such a criterion. But he had a try and it immediately worked.
In the age of paper media, there was no shortage of eye-catching tabloids, either. However, they could not deliver much impact given their irrational style and poor circulation transparency.
By contrast, in the Internet era, traffic data can be clearly presented in an unprecedented way, and becomes a KPI directly concerning the income of online editors and journalists.
Five years later, similar frustration was also felt by editor Lyala, when she job-hopped to Baidu from a state-owned media outlet.
Data generated by Baidu was much more detailed than what Chen had got: in addition to approximate clicks and browsing history, it offered defined user profiles, as well, making targeted audience crystal clear.
Lyala was responsible for pushing articles and optimizing headlines based on real-time data, and at the same time generating weekly report, and calculating daily workload and particularly traffic increase in Excel.
She couldn’t fit in at first, because she habitually selected topics based on the criteria learnt at her university and previous employer, which, of course, didn’t work well.
Later, she accidentally posted a few cheesy pieces about tigers mauling tourists in a zoo, which turned out to be a sensation. Since then, she started to hunt for and push such “overdramatic” stories, which repaid her with the highest traffic flow in her team.
She sometimes felt uneasy about what she did. After all, she had received a very professional journalism training at university. But the increasing traffic flow gradually appeased her. And she argued, “It’s more realistic to finish this chart than wonder about news value.”
Algorithm-enabled news tool:
Later, machine and data have been further upgraded and information display efficiency has been greatly improved, bringing about an era of algorithms.
In theory, with articles pushed to the targeted readership, user satisfaction would be higher, which is seemingly crystallized by the meteoric growth of traffic flow and the time users stay on news aggregator Jinri Toutiao.
Pan Luan, a partner of social networking app “Zuiyou (最右)” seemed to agree. “Before Toutiao, was there anyone capable of sending all information of one club or one football player to me?” asked he.
What Toutiao is doing also corrects traditional media’s single elite perspective.
According to Wu Da, senior director of operations at Toutiao, when he worked at the new media department of Southern Weekly, he and his colleagues used to wonder who should be the perfect spokesperson for an online game designed for workers at factories like Foxconn.
Their answer was Han Han (a best-selling novelist in China), but it turned out to be the Phoenix Legend, a Chinese music duo popular among migrant workers, but is not appreciated by the well-educated. In fact, a famous journalist of that paper even claimed to have never heard of that music duo before.
Looking back, Wu Da believes that in an environment staffed by well-educated and like-minded journalists and editors like Southern Weekly, “information exchange with other circles of life is bound to be slow.”
In the era of algorithms, despite the ever-increasingly detailed user profile, user-feedback indexes remain scarce, which only include user behavior and traffic flow derived from pageview, session length and number of daily active users.
Many argue that algorithm-enabled tools excessively cater to individual preferences and therefore can do nothing but encourage superficial desires.
Algorithms have a profound impact on content creators, too. Four years ago, Zhang Yiming, founder of Toutiao impressed Wu Da by saying “content producers will scale down; large media outlets with hundreds of employees will be replaced by those with a staff of no more than 20, or even only 5 to 8.”
