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News and Media: Algorithms and social media

Algorithms explained

My computer knows what I want to see!

Do you think the information you see when you scroll through your feeds on social media or search engines appear by chance? Do you think the information you encounter is objective and you see everything that's available? You may not be seeing the whole picture as algorithms can pre-determine what you view. 

An algorithm is a set of instructions designed to perform a specific task. 

Algorithms may provide search results, content recommendations, or targeted advertisements based on an individual user's past actions, as well as by grouping an individual user in with a representative cohort. Many social media algorithms are used to understand user habits and to identify patterns and make predictions about user behaviour.

Understanding algorithms

What do I need to know about algorithms?

Algorithms can reinforce existing biases, especially on social media.

Take a look at this example: your friend has posted an article on Facebook on a particular topic. You click on the article to read it. This click lets Facebook know (i.e. the Facebook algorithm) that you are interested in that topic. In future, Facebook may structure your news feed to include more sources on that topic and filter out other sources that may give you a different viewpoint on that topic. This can lead to a 'filter bubble' so that you only see information that align with your existing beliefs.  Find our more about filter bubble in the box below. 

When you're online and using search engines or social media, you need to think about...

  • the inherent biases in computer programming - the existence of the algorithms and what they perform/tasked to do
  • always evaluating the information you encounter online
  • never assuming that the number one/highest ranked result is always the best result
  • your privacy - understanding that when you conduct a search on digital platforms, the algorithms are working in the background to tailor what you see now and in the future

Take a look at the following article for further information on social media algorithms:

Rage machine - how social media algorithms are changing our behaviour. - Darius Pocha 

Filter bubble

closeup photo of two bubbles

Filter bubble - what is it?

Eli Pariser (author of The filter bubble: what the Internet is hiding from you) came up with the term 'filter bubble'. In it's simplest form, a filter bubble is when your online experience is personlised due to your previous online activity.

Do you search for information online? Have you noticed that any promotions and advertisments are for the exact thing you've searched for? You are in a filter bubble. Take a look through the following tabs to know what this is and how to burst that bubble!

How is this done?

A filter bubble is created by online avenues such as websites, search engines and social media feeds using algorithms or a set of rules that personalise (or in other words, selectively guess!) what you see due to your search history, what you've clicked on previously - shared, commented on and liked - and also your location. That is, you only find online results that mirror your opinions and viewpoints. You are then trapped in a 'filter bubble' and not exposed to information that could broaden your opinions or viewpoints. 

Why should I care about this? 

Don't get caught in a filter bubble. As a student researching a topic, you need to be able to access important information or alternative opinions and viewpoints. Being in a filter bubble could impact your success in gaining a full insight into your topic area if what you see if filtered.

Sourcing information requires you to see the whole picture. Pariser reminds us to find information that:

  • Makes us uncomfortable
  • Is challenging
  • Is important
  • Presents other points of view

iridescent bubbles

To ensure you see the whole picture when you are searching for information you can try the following steps below.

Take control and burst that filter bubble to get the most variety of information by:

  1. Using the library's databases - Primo does not pre-filter your results based on your search history or online activity
  2. Deleting/clearing your browser cookies
  3. Deleting your search history
  4. Keeping your data private - look at your privacy settings and amend accordingly
  5. Switching off targeted advertisements and promotion
  6. Searching the web using incognito browsers
  7. Checking and evaluating your sources
  8. Opting out to share your data on all online services that you subscribe to such as Facebook, Google, and Instagram