Spend any amount of time on Chinese social media and you’ll almost certainly come across a curious phrase: “Send you trending.” The line is ubiquitous on reports of serious social injustices, such as companies that defraud their consumers. It’s shorthand for a movement, users’ way of promoting the rapid spread of information in order to effect social change.

The mechanics are relatively straightforward. Most Chinese social media sites maintain a list of “Trending” topics. In theory a collection of the most popular and discussed keywords at a given moment, they are selected and displayed according to the platforms’ often opaque algorithms. Although typically dominated by entertainment news and gossip, the lists are still subject to a degree of user control, and topics with enough likes and comments can rocket up the chart quickly. Once there, they are seen by all users on the platform, allowing them to generate significant public attention and discussion.

This means that the spontaneous behavior of netizens commenting “Send you trending” can be seen as a kind of resistance to the existing algorithm sorting logic through collective action. At the heart of this resistance is the struggle for visibility, with different interest groups attempting to increase their public visibility and social discourse power.

Let’s take a look at one typical case. On May 7, 2022, a user on microblogging site Weibo posted a video accusing a faculty member at Nankai University of engaging in an improper relationship with a student. The video attracted a large amount of traffic to the comments, and support quickly spilled over from the original post to the university’s official Weibo account. Soon, keywords like “Nankai University” and the faculty member’s name soon began to trend. Posts with related terms quickly exceeded 100 million views, hovering around the 11th position on Weibo’s trending list.

On May 8, these terms were removed from the Trending section, and Nankai University’s official Weibo account closed comments on its posts. Two days later, Nankai University told a reporter with China News Weekly that it was investigating the incident and would handle the matter. This quickly prompted the appearance of a new phrase — “Nankai University Responds to Signed Allegations Against Its Teacher” — on Weibo’s trending page before this tag, too, was taken down on May 11.

This case didn’t end there, however. On May 13, after turning on comment protection, Nankai University announced the results of its investigation, including punishments for three faculty members. By May 15, the hashtag combining Nankai University and the accused teacher’s name had been viewed more than 220 million times and generated over 700,000 interactions — numbers that came in large part in spite of the platform’s interference.

Success in this battle requires constant tactical refinement, and social media users are constantly developing new approaches to try and game the algorithm. One such tactic is “encryption,” whereby users create coded methods of communication to avoid their messages being automatically filtered out by algorithmic detection technology. These include the use of abbreviations (such as “NK” for Nankai University), inserting punctuation marks into sensitive words (such as “sex/ual assa/ult”), using special expressions or symbols (such as deconstructing Chinese characters into their constituent parts), or sharing text screenshots.

Another tactic is “appropriation,” in which users pursue algorithmic visibility by actively clicking, sharing, commenting, adding hashtags, and paying for memberships to leave a trail of data that the algorithm can analyze.

In addition, users can achieve more productive results through the use of tactics like “relay” and “bricolage.” Relay refers to when many different users post the exact same text. In the process, users demonstrate a spontaneous connection and community awareness. While the platform will sometimes delete accounts engaged in relaying info, users will typically encourage each other to keep it up, creating a kind of collective identity that, no matter how unstable or imagined it may be, works to unite participants and build momentum.

Meanwhile, “bricolage” is demonstrated by the creative use of platform features by users, such as taking over the comment sections of unrelated news reports, or linking related topics with events that are trending in the same period. For example, during the Nankai University incident, netizens linked the university with topics such as Mother’s Day and the 2008 Sichuan earthquake. One original post with multiple hashtags said: “Today is Mother’s Day and I’m so angry with your university that I can’t sleep... What are women in 2022? Does every victim have to be humiliated this much before they can be heard?” Online posts like these are designed to gain greater discourse space and social support for related issues.

Overall, algorithmic resistance is a form of self-organized, collective action by grassroots users that works to fix the unfair visibility politics of platforms and to express a demand for social justice. Of course, this kind of spontaneous resistance suffers from a lack of sustained critical reflection, and users have neither the motivation nor the ability to continuously engage. Netizens’ comments are often irrational and emotional, and more closely resemble a cathartic response than a meaningful, coherent outpouring. Some even contain violent remarks, which drift from the original intention of fighting for justice and personal dignity.

Finally, it has to be said that ordinary netizens participate in algorithmic resistance out of dissatisfaction with online visibility as controlled by platform algorithms. However, their method of resisting involves actively participating in the competition for algorithmic traffic and so further integrates them into the existing algorithmic sorting mechanism, which then contributes even greater traffic to platforms. Ironically, the biggest beneficiaries of algorithmic resistance might be the platforms themselves.

Translator: David Ball; editor: Wu Haiyun; portrait artist: Wang Zhenhao.

(Header image: Ramas/VectorStock/VCG, reedited by Sixth Tone)