PROJECT SUMMARY
Assessing the Personalisation of Search Results from Major Recommendation Engines
Focus Area(s): News and Media
Research Program: Data
There is a lot of speculation about the impact that search engines have on the information we encounter. Search engine personalisation may be influencing individuals’ search results, and thereby shape what they know of the world. This may affect their personal decisions, and our collective decisions as a society – from how we spend our money or who we vote for to our attitudes on critical issues such as the safety of COVID-19 vaccines.
This research aims to assess the extent to which search results are personalised, by various leading search engines and their algorithms, based on the profiles established by those search engines for their different users. It compiles and analyses the search recommendations encountered by a wide range of genuine users across prominent digital media platforms, for a variety of generic and specific topics, and over a period of time.
This research advances earlier experimental work by our partner organisation AlgorithmWatch, using ‘data donation’ methods via browser plugins and other tools, to involve the public in the research. This research evaluates the potential social impacts of search personalisation, including its potential for creating ‘filter bubbles’, promoting misinformation and disinformation or increasing political polarisation. Findings from this project will inform policymakers, educators, and the platforms themselves to mitigate any negative effects of information shaping online.
PARTICIPATE
Become a citizen scientist and join the Australian Search Experience project
When you use a search engine, do you see the same results as your colleagues, friends, or family do? If not, why is that? Are search results personalised especially for you? If so, what are the criteria? Which topics do search engines suggest to you and other users?
We want to find out. With your help.
To participate in this project visit The Australian Search Experience webpage
RESEARCHERS
PARTNERS
AlgorithmWatch
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