Assessment 3

Algorithms as cultural intermediaries

MECO6936 Social Media Communication

Name: Yuan Liu

SID 480225638

Tutor: Jennifer Hagedorn   Tuesday 8AM – 11AM


In the advent of Web 2.0, online social media has burgeoned and spread at a rapid speed. The need for cultural intermediaries also grew along with the demand for translation between cultural capital to economic capital by the audience and the companies.

As more and more people gradually have access to the internet, the data they created also increased at an astonishing speed. In order to adapt to this fast-paced development on the internet and social networks, the workload faced by companies and cultural intermediaries is increased too. It became hard for Traditional cultural intermediaries to handle the work because they can no longer handle these works by themselves manually 24 hours a day. People need a new way to process the huge amount of data creating by the users. Therefore, the algorithms, which can help people to categorize and statistic data, became to play an increasingly important role in social media and on the internet as cultural intermediaries.

Main Concept

What is cultural intermediary?

Lots of experts gave their definition to Cultural intermediaries. In class, the video from Jonathon Hutchinson mentioned that “Cultural intermediaries are the agents who are located in the middle of cultural production. They are the agents who facilitate the process of co-creative media production.” Adkins (2011) explain the concept of cultural intermediary in her article Cultural intermediaries she explained that cultural intermediary refers to ‘those sets of occupations and workers involved in the production and circulation of symbolic goods and services in the context of an expanding cultural economy in postwar Western societies.’ As Bourdieu (1986) mentions in his book, cultural capital could be translated into other forms of capital. From this perspective, Hutchinson (2017) gave the definition of cultural intermediaries’ that cultural intermediary is the capital translators who have the abilities to understand messages from producers and deliver them to its audience effectively. In all, cultural intermediaries are the agents between institutions, organizations and the

Figure1 examples of cultural intermediary.  (Hutchinson, 2019)

What is algorithm?

The notion of algorithm in mathematics can date back to ancient Greek (Cooke, Roger L. 2005). For algorithm in computer science, it can date back to decades ago. Rogers (1987) once explain it that “an algorithm is a procedure for computing a function (with respect to some chosen notation for integers) “. While Striphas explains it as “the sorting, classifying and hierarchizing of people, places, objects and ideas” in the computational process.” (Striphas, 2015). In all, the algorithm is a series of actions, such as identifying and categorizing the content, taken by computer based on the data provided by users in order to achieve a certain purpose.

Figure 2 example of recommended algorithm. (Nykjaer, 2019)

How it works in social media?

In our daily use of internet or social media platform, the most common use of the algorithm is the content recommendation. The algorithm helps companies and institution to process the huge amount of data they collected from the users. In the perspective of the algorithm. It creates algorithmic identities for all users. As Cheney-Lippold (2018) put it “In other words, online you are not who you think you are.” Then, based on these algorithmic features, it calculates and analyzes the pattern of the users’ viewing history and then send relevant content to each user. In this way, there is a great chance that their user would prefer and accept the recommended contents to them. By applying the algorism in the social media platform, “intermediaries can have a new and nuanced view of cultural habits occurring across communication environments. in front of the algorithm.” (Cheney-Lippold, 2018). The way the algorithm works as a cultural intermediary is similar to human cultural intermediaries. As Hutchinson (2017) mentioned, the algorithm first helps quantitative social network analysis (SNA) by capturing the data from the internet. Then it helps to clean and visualize the data. Based on these data, the algorithm can calculate the final result according to different purposes and different targets.

Case study about how it works.

Nowadays, nearly every social media platform recommend content based on their algorithm. The platform will recommend relevant content according to your viewing history and those content you spent more time on them. Sometimes, they can even guess the potential content which you might prefer based on their algorithm. Take Instagram, the primary focus in our welcome week campaign, as an example. In its searching page, Instagram will show all the pictures and short videos you might like based on user’ viewing and searching history. Here, the algorithm works as the agent. It finds the cultural productions which it considered would be an appeal to you and translate it into economic capital. In another way of speaking, the content that the algorithm provides to you is the advertisements.

Figure3,4 examples of the different recommended content on Instagram

How the algorithm as cultural intermediary applies in our campaign?

 So, follow this idea, in our welcome week campaign, #youtoohavethepower, we use the recommended algorithm as one of our ways to reach more people. In the campaign, “the welcome week of the USyd” is one keyword for the social media platform so that everyone, who search for this topic, can reach to the content. Also, we add popular superhero element to our campaign as our main theme, according to the big heat of Marvel and DC movies. The algorithm here on the social media platform will play the role of our agent who advertises our cultural content to the audience. Once the algorithm spots someone who is interested in superhero content or our keyword, it will automatically recommend our content to the audience’s list of recommendations. In this way, the algorithm plays the role of cultural intermediary as it works as the agent who helps us find our main audience and find out what content our audience preferred.


  The algorithm as cultural intermediaries is necessary and crucial in today’s society because the human cannot deal with those huge amounts of data in such short and limited time. The efficiency algorithm provides is irreplaceable, and as the development of algorithm and internet, the algorithm as cultural intermediaries has deeply rooted in our daily life.

However, even using algorithm is now one of the most effective ways to disseminate the cultural content and to translate cultural capital into other forms of capital, it still has potential risk for the society and for the audience. As Striphas (2015) points out, “culture and the media systems that create, distribute and perpetuate an algorithmic culture are at risk of limiting public culture in favor of an elitist cultural re-appropriation.” Furthermore, due to the imperfectness and incompleteness of the algorithm, it may cause a recession of cultural multiformity. For example, the famous app Tiktok has faced a similar problem. Once their user viewed a certain type of video, the algorithm will recommend a similar type of content to him or her endlessly. In the end, it will develop like a snowball that user can only see one type of content.

In the future, I believe the algorithm will continue to be the major cultural intermediaries in our social media platform and on the internet. However, what difference is that it will become more intelligent as the development of big data science and other High technologies such as artificial intelligence and quantum computer. And the most important thing is that it will serve the users well in a more mature and humanizing way.

Word count:1243


Adkins, L. (2011). Cultural intermediaries. In D. Southerton (Ed.), Encyclopedia of consumer culture(Vol. 1, pp. 389-391). Thousand Oaks, CA: SAGE Publications, Inc. doi: 10.4135/9781412994248.n147

Bourdieu, P. (1986). The Forms of Capital. In R. J. G., Handbook of Theory and Research for the Sociology of Education (pp. 241–258). New York: Greenwood Press.

Cheney-Lippold, J. (2018). We Are Data: Algorithms and the Making of Our Digital Selves. European Journal Of Communication, 33(1), 110-110. doi: 10.1177/0267323117753751c

Cooke, Roger L. (2005). The History of Mathematics: A Brief Course. John Wiley & Sons. ISBN 978-1-118-46029-0.

Hallinan, B., & Striphas, T. (2014). Recommended for you: The Netflix Prize and the production of algorithmic culture. New Media & Society, 18(1), 117–137. doi:10.1177/1461444814538646

Hutchinson, J. (2017). Cultural Intermediaries. [S.l.]: Palgrave Macmillan.

Hutchinson, J. (2019). The role of the Cultural Intermediary within professional participato…. Retrieved from

Maguire, J., & Matthews, J. (2012). Are we all cultural intermediaries now? An introduction to cultural intermediaries in context. European Journal Of Cultural Studies15(5), 551-562. doi: 10.1177/1367549412445762Nykjaer, K. (2019). How does the Amazon recommendation system work? – Analyze the algorithm and make a prototype that visualizes the algorithm. Retrieved from

Striphas, T. (2015). Algorithmic culture. European Journal Of Cultural Studies18(4-5), 395-412. doi: 10.1177/1367549415577392

Rogers, Jr, Hartley (1987). Theory of Recursive Functions and Effective Computability. The MIT Press. ISBN 978-0-262-68052-3.

4 thoughts on “Algorithms as cultural intermediaries

  1. Hi Yuan:

    Very thorough analysis and explanation of how algorithms work as cultural intermediaries. As you said, the algorithm is used for content recommendation, while a lot of people start to worry about their privacy, because the algorithm cannot work without access to their information, such as locations, contacts, and search history. Even though there are some regulations on to what extent can social media company use people’s data, it is still questionable that if some data will be leaked or hacked. I also agree with what you said about how algorithms can calculate and analyze the pattern of the user’s viewing history and then send relevant content to each user. Nevertheless, sometimes the algorithm might oversimplify the users because the system cannot input the user’s real-time emotion in the recommendation mechanism. For instance, Spotify can identify its user as a hip-hop lover, while the user might sometimes want to listen to some relaxing genre, such as Jazz, when they feel stressed. However, the algorithm will recommend playlists based on the most frequently played music, so that might make the user unpleasant. It is true that the algorithm is a powerful tool to distribute information, but there are still aspects need to be developed.


  2. Hi Yuan
    You’ve conducted a deep analysis of the concept of algorithms as cultural intermediaries on social media platforms. I really appreciate that you take the recommended content on Instagram homepage as an example to vividly show how the algorithmic system on social media platforms acts as an agent to promote advertisements to audiences. As you mentioned in your article, because the massive data created by users could not be processed only by traditional cultural intermediaries, more and more companies tend to use algorithms as a tool to promote their products. In China, one social media and e-commerce application focusing on cosmetics called RED, also known as XiaoHongShu, has also succeeded in relying on algorithm as a cultural intermediary to recommend fashion items to its audiences on some specific advertising areas of their homepage. I also agree that algorithm still has potential risk for the society and the audiences. Besides the recession of cultural multiformity, abuse of algorithm could also lead to filter bubble which isolates audiences from opinions or information that they are not interested in.
    Furthermore, it is quite remarkable that you’ve applied this concept to your own social media campaign. As I’m also a fan of Marvel, I’m quite interested in how you involve superhero elements in your campaign! Hope to have further communication with you!


  3. The blog – Algorithm as Cultural Intermediaries – has been well written as it has explained how algorithms affect cultural intermediaries and it has also given examples. Yuan Li has taken strides in defining what cultural intermediaries and algorithms are and also used images which can offer great insight to the definitions. The author has also well referenced his sources, and this proves that he did research and understands the topic. The blog has linked up the relationship between algorithms and cultural intermediaries and how they work in real life. He explains how algorithms assist companies and institutions process the huge chunks of data they collect from users. Li also likens the functionalities of cultural intermediaries to human cultural intermediaries. The blog explains how algorithms visualize data and how they calculate the final results based on purposes and different targets. It also gives an excellent example of an application of algorithms in a cultural intermediary – a search engine of Instagram. The search engine of Instagram is based on the algorithms that predict what the users want based on what they like, their search history, and potential interest. It is an excellent example that many people can relate with and understand how algorithms work in cultural intermediaries.


  4. The author suggested algorithms as cultural intermediaries have acted an essential role in process data with the need for fast-paced development social networks. He defined the notion of cultural intermediaries and algorithms and then demonstrating how these concepts work to engage target audiences in social media practice taking the campaign on Instagram as an example. I agree with social media platforms have applied algorithms to recommend relevant contents, and the potential liked contents based on the user’s past content consumption or search queries. As he mentioned, cultural intermediaries are the agents among institutions, organizations and audiences, and that is how algorithms do – helping organizations to deliver personalized and popular messages to the niche markets. The article emphasized Instagram’s algorithms acts as an agent/cultural intermediary in the O-week campaign advertising relevant contents to his target audiences. However, social media algorithms are complex machine learning process rather than one inherent pattern. For example, Instagram’s algorithms prioritize quality and relevancy to display the most popular contents to the largest group of people, while Facebook focuses more on meaningful interactions to encourage conversations. For the O-week case in a relatively small-scale community, the most suitable platform to link with the theory can be taken into considerations. I agree with what other comments mentioned, the article is well-structured and illustrated how social media algorithms work. Thank you for sharing.


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