Giving Compass' Take:

· RAND Corporation examines the factors influencing what we see online and explains that our actions are the biggest determinant of the content we see while algorithms only play a small part of that process.

· How do social media platforms collect and use personal data?  What information privacy policies are in place to protect users? 

· Check out these questions to drive effective data use

When the Cambridge Analytica scandal broke in early 2018, people were surprised to discover the extent to which their personal data, online behaviours and preferences had been used to target them for political advertising on Facebook.

It prompted outrage and the UK's Digital, Culture, Media and Sport Committee, which investigated the scandal at the time, expressed concern over the “relentless targeting of hyper-partisan views, which play to the fears and prejudices of people, in order to influence their voting plans.” This concern over social media profiling and targeting remains in the news, with examples including the claim that YouTube's algorithms and filtering software may help to “radicalise” viewers, and assertions of algorithms being as influential as policies in the 2019 UK general election campaigns.

But does the issue merely lie with how social media platforms use algorithms to deliver content online?

Algorithms are at the core of the decision-making process for social media platforms such as Facebook and YouTube as they determine the content that people see and engage with online. This is designed to maximise user engagement by prioritising content that is most appealing to the users and considered to be most relevant to people's interests. This filtering is based on user interactions with these platforms and their account and behavioural data. The platforms collect this data continually and use it to help predict users' behavioural patterns and decision-making processes.

The online platforms use this data to target advertisements, determine the content shown and influence users' buying decisions. The challenge is not a lack of awareness from users about their data being collected, but rather concerns about what that data can be used for, the sophistication of the algorithms and the accuracy with which they can predict users' responses and behaviour.

Read the full article about data collection and analytics by Tor Richardson-Golinski, Amelia Harshfield, Advait Deshpande at RAND Corporation.