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Antagonism with Algorithm: Human and Nonhuman Actors on the Movie Comment Site

Early November 2020, the Chinese translation of Russian novel Memory Memory (Памяти памяти) was published. Two days later, its editor Luo found that there have been more than 200 people labelled this book as ‘Have Read’ and left short comments on Douban. ‘The word count of Memory Memory is more than 310 thousand,’ Luo complained in her Douban post, ‘More than 200 people have finished it in less than a week, it’s nearly impossible for an abstruse book’. She found that most of those comments are either copied from others or made up with irrelevant nonsense. In most of the cases, the accounts left these rubbish comments are new and related to Wang Yibo, a Chinese actor and celebrity.

[1]Wang Yibo
It might be confusing that why Wang’s fans leave rubbish comments to such an irrelevant minority book. Let’s go back to the beginning: what is Douban and how it works?

Douban is a social networking platform and an online database, providing information about books, movies, TV series, games, music, stage plays and so on. Like IMDB and Rotten Tomatoes, Douban has a scoring system, in which the marks given by the audiences or readers will be calculated and displayed. The rule is that scores given by different users have different weight in the calculation,  instead of ‘one ticket per person’. Douban has an algorithm to evaluate the accounts to keep the score more authentic. The more active and regular the accounts are, the more weight they have. The comments given by newly created accounts will be automatically collapsed. It seems reasonable, for now, but the problem is that people are always looking for a way of ‘breaking’ or even ‘making use of’ the algorithm.

To make the score of Wang’s upcoming movies high, his fans will leave high scores and positive comments to them with several different accounts. After creating accounts, they make the accounts seem more ‘active’ by posting, scoring, following other users. That is called ‘cultivating the accounts‘. According to the instruction given by a CEO of an entertainment consultancy, cultivation of the accounts has six key points:

  1. The avatar or nickname should not directly relate to any celebrity;
  2. Actively follow each other;
  3. Join several Douban groups, maintain a certain level of activeness in the groups;
  4. Complete 30 short and 3 long reviews;
  5. Rate other works in the 2-4 star range, neither too high nor too low;
  6. Do not rate films/books that have not been released.

It takes about two months for the above processes to continue before an account get enough weight in the algorithm and is considered ‘mature’. The fans tend to choose newly published or minority books as their ‘tools’ of cultivating accounts. After being criticised as ‘lacking respect’ and ‘disrupting the platform’, they turn to the ancient masterpieces like Dream of the Red Chamber.

From a sociology perspective, the most interest point of this event is that human beings are now tangled with nonhuman factors deeper and deeper. Some theorists (Castells, for example) look at the digital society from the network society approach, which views people as nodes and emphasis how and with whom they are connected. While some others, like Latour, suggested that there is no binaries of human culture and nonhuman nature. Nonhuman actors matter as much as humans do in the social network, and human plays a vital role in the object web as well (Law, 2008). This is one of the essential viewpoints of Actor-Network Theory (ANT). ANT is the reaction to the downplay of human actors in natural sciences and of nonhuman actors in social sciences, reconsidering what ‘thing’ is and what is its agency (Muniesa, 2015).

Now think about Douban. Obviously, it only makes sense when the score of a book can reflect its quality, which means all the marks and comments come from real readers. For social networking sites, the most ideal situation is that users interact with each other as they do in the offline world. People do not have to be aware of the existence of the data, the algorithm and other technologies behind their chat. But in fact, users also interact with the nonhuman actors, and in many cases consciously.

It is not a new phenomenon. When online shopping and advertising emerged a few years ago, ‘click fraud’ came with it. ‘Click fraud’ means clicking a link or liking a Facebook post without real interest in it. These were mostly done by automated script and computer program, and sometimes by a human. Program versus program seems fair.

Then social network platforms fought back: Douban uses the weight evaluation system, Weibo uses the personal credit score. Their aim is to minimise the impact of these dross contents, making the expression and communication more ‘human-like’. then people began ‘cultivating the accounts’, replacing the scripts and programs with the human. Chinese fans sometimes call themselves ‘data workers’ in a self-deprecating tone for their mechanical and repetitive operations. The work is tedious because they are actually fighting the algorithm rather than those who leave negative comments.

Douban’s response to the event is that they will enhance manual check. From where I see it, it is ridiculous because the scripts, programs and algorithms are created to easing the burden on human.  Now human joins the battle because the program cannot do its job. Now the balance is broken, quite a large proportion of the content you can see on the social network platform is nonsense. AI helpers like Siri and Alexa can talk like a human, human are producing messy codes like a broken-down computer just for making their 12th Douban account weighs more in the algorithm.

The difference between online and offline interaction is more clear from the ANT approach. The technology is not only the tool for the human but also an actor in the networks. The algorithm is designed to encourage some behaviours and discourage others, the Internet users find a way to cheat it, the algorithm improves, then people find another way of cheating. It is a circle, but the methods of interacting are continuously being shaped in this process. After all, you would definitely not comment on a book with meaningless words to make yourself more credible when giving a movie recommendation.

 

 

References

B. LatourReassembling the Social: An Introduction to Actor-Network-Theory
Oxford University Press, Oxford (2005)
John Law. (2008). ‘Actor Network Theory and Material Semiotics’ in Turner, B (eds.) The New Blackwell Companion to Social Theory | Wiley Online Books [WWW Document], n.d. URL https://onlinelibrary.wiley.com/doi/book/10.1002/9781444304992#page=156?casa_token=iJSGI_7O41IAAAAA:o87nVWnNbP3n5f0wDz3RQLp9aFktjUMPG_v6ZKRiUl1lGxV96QHSb8g3-IBTDH6YLi5F7QKhhXyDZg (accessed 11.27.20).
Muniesa, F., 2015. Actor-Network Theory, in: Wright, J.D. (Ed.), International Encyclopedia of the Social & Behavioral Sciences (Second Edition). Elsevier, Oxford, pp. 80–84.
https://doi.org/10.1016/B978-0-08-097086-8.85001-1
“饭圈”刷屏又换战场?这次是?(Fans flood the screen elsewhere?) -中新网 [WWW Document], 2020. . archive.is. URL http://archive.is/Q3Qf7 (accessed 11.27.20).
证券日报网-“饭圈”文化入侵豆瓣 起底吸血豆瓣账号的黑产交易(The cultural invasion of Douban by the “fans circle” and the dark trade of Douban accounts)
[WWW Document], 2020. . archive.is. URL http://archive.is/zXOF8 (accessed 11.27.20).
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