PROJECT SUMMARY

The Australian Search Experience 2.0

Focus Areas: News & Media
Status: Active

The first phase of The Australian Search Experience project launched in late July 2021 and over 12 months collected over 350 million search results from more than 1,000 participants. Results from phase 1 showed that personalisation of results for generic queries in major search engines is minimal, and generally limited to ensuring geographic relevance for users. Yet partisanship is rife. Eight billion queries are issued daily to Google alone, and many partisans use search engines for fact checking, can it really be that this ubiquitous ADM plays no role in the growing partisanship of society? 

The Australian Search Experience 2.0 will address a critically overlooked part of the story. We already know individual searchers formulate their queries very differently, and that this directly affects the results obtained, but understanding the extent and form of query variation as well as its impact is methodologically challenging.

The query is one of the key means people have to control not just search, but with the rise of generative AI, text queries and instructions are becoming the dominant way that ADM systems are controlled. 

When considering the impact of search on society, we know that individual searchers formulate their queries very differently, and that this directly affects the results obtained.

This project will generate significant new knowledge about the breadth and quality of information returned in response to diverse search queries, and offers a significantly more realistic perspective than past research for the impact of variations in users’ queries on the results recommended to them. It will significantly advance the state of the art in the field by developing novel methodologies for the study of search and recommendation in conventional (text-based) and emerging (voice-based and AI assisted) search interfaces, and producing new insights into their impact on users and content creators.

Findings from this research will have both productive and preventative implications: a better understanding of query diversity for a given topic will enable the designers of textbased and non-text-based search interfaces to enhance the ability of such interfaces to produce quality results; similarly, it will also enable educators and non-profit organisations to develop more targeted interventions for improving search literacy and preventing the spread of misinformation.

PROJECT OBJECTIVES

  • Explore novel ways of measuring effectiveness of search engines, by considering a diverse pool of demographic groups that represent the breadth of the Australian population, and observing their approaches to developing search queries;
  • Evaluate the range of search results that such queries return using AI to simulate the full diversity of search queries on controversial topics;
  • Develop an understanding of how non-traditional search interfaces and contextual factors drive query variation; and
  • Determine relationships between queries and search results for specific types of query, public interest topics and key news and information sources such as Wikipedia projects.

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RESEARCHERS

ADM+S Chief Investigator Mark Sanderson

Prof Mark Sanderson

Project Co-Leader and Chief Investigator,
RMIT University

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Axel Bruns

Prof Axel Bruns

Project Co-Leader and Chief Investigator,
QUT

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Daniel Angus

Prof Daniel Angus

Chief Investigator,
QUT

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Danula Hettiachchi

Dr Danula Hettiachchi

Associate Investigator,
RMIT University

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James Meese

Assoc Prof James Meese

Associate Investigator,
RMIT University

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Ariadna Matamoros Fernandez profile picture

Dr Ariadna Matamoros-Fernández

Associate Investigator,
QUT

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ADM+S Chief Investigator Falk Scholer

Prof Falk Scholer

Associate Investigator,
RMIT University

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Dr Damiano Spina

Dr Damiano Spina

Associate Investigator,
RMIT University

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Johanne Trippas

Dr Johanne Trippas

Associate Investigator,
RMIT University

Maarten de Rijke

Prof Maarten de Rijke

Partner Investigator,
University of Amsterdam

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ADM+S professional staff Abdul Obeid

Dr Abdul Obeid

Data Engineer,
QUT

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Amanda Lawrence

Dr Amanda Lawrence

Affiliate,
RMIT University

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Natali Helberger

Prof Natali Helberger

Research Partner,
University of Amsterdam

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Judith Moller

Prof Judith Möller

Research Partner,
Hans Bredow Institut

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Kim Osman

Dr Kim Osman

Research Partner,
QUT

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PARTNERS

ABC logo

Australian
Broadcasting
Corporation

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AlgorithmWatch logo

AlgorithmWatch

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Hans Bredow Institut Logo

Hans-Bredow-Institut

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University of Amsterdam logo

University of Amsterdam

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