Investigating Google’s Search Engine

Rosie Graham is Lecturer in Contemporary Literature and the Digital at the University of Birmingham, UK and co-director of its Digital Cultures Research Centre.

Introduction: Investigating Google’s Search Engine

1.0 Google’s Dominance

2.0 The Three Steps of How Search Engines Work: Crawling, Ranking, and Query Results
1.1 Step One: Crawling
1.2. Step Two: Ranking
1.3 Step Three: Query Results

3.0 Five Key Challenges of Studying Google’s Search Engine
3.1: Multiple Actors: Search Engine Optimisation and Economic Incentives
3.2: Moving Targets
3.3: Each Search a Partial Viewpoint
3.4: No Real Alternatives
3.5: The Myth of Black Boxes

4.0 Chapter Outlines

5.0 Notation and Examples

Chapter One:
Understanding Google Queries and the Problem of Intentions

Introduction

1.0 Categorising How and What People Search
1.1 The Roles of Search Engines and Information Retrieval’s Question of Why
1.2 Query Length and the Problems of Intention
1.3 All Information is Ethical: Searching for [food for snakes]

2.0 Predicting Intentions with a Lack of Information: Plato, Gadamer, and Derrida
2.1 Gadamer’s Hermeneutics and Plato’s Fears of Deception
2.2 Google’s Algorithms and Derrida’s Monster

3.0 What Kinds of Things Do People Search Google For?
3.1 Google Trends, Brexit, and “Frantically” Googling after the EU Referendum

Conclusion


Chapter Two:
Google’s Impact on Cognition and Memory: Histories, Concepts, and Technosocial Practices

Introduction

1.0 Google’s Impact on the Cognition and Memory
1.1 Metaphors of Recall from Extended Minds to Transactive Memory

2.0 Technosocial Memory Practices from Oral Culture to Digital Literacy

3.0 The Legacy of Naturalised Technologies
3.1 Truth and Knowledge for Plato
3.2 Aristotle’s Sensory Approach

4.0 Technosocial Memory Before Google: The Ars Memoria
4.1 The Science and Magic of Search

5.0 Treating the Mind as Technology: Bacon, Hooke, and Modern Psychology

Conclusion


Chapter Three:
Autocomplete: Stereotypes, Biases, and Designed Discrimination

Introduction

1.0 The Desire for a Digital Oracle
1.1 Autocomplete’s Minimal Academic Attention

2.0 The Biases of Autocomplete: Stereotypes and Discrimination

3.0 Predicting and Shaping User Attitudes: The Origins of Autocomplete
3.1 So, How Does Autocomplete Operate?

4.0 Second-Order Stereotyping: Sexist Suggestions for Female Scientists
4.1 RankBrain and the Biases of Machine Learning
4.2 Automated Misogyny for Every Individual

5.0 Speed
5.1 Speed and Judgment: Time to Reflect

Conclusion



Chapter Four:
Google’s Search Engine Results: What is a Relevant Result?

Introduction

1.0 “Quantifiable Signals” and Malawian Witch Doctors

2.0 What Should Search Engine Results Be?
2.1 The Idealists: Search Is Democratic, Relevance Can Be Measured Objectively, and Answers Can Exist Independently of Bias
2.2 The Difficulty with Measuring Relevance
2.3 The Contextualists: Search Is Undemocratic, Relevance Is a Measure of Personalisation, and All Answers Are Inherently Biased
2.4 Are Search Results Personalised?

3.0 Methodological Challenges of Studying Search Engines
3.1 Particular Considerations for Collecting Search Engine Results

4.0 Variables that Matter: Search Experiments in 2015, 2017, and 2021
4.1 The Rationale Behind Focusing on Same-Sex Sexual Orientation
4.2 Queries Used
4.3 Capturing the Spread of Results from the First Page
4.4 Evaluation Method

5.0 Google’s Public Position on How They Provide Results

6.0 The Importance of Language and Location in Search Results (2015)
6.1 How Do Variations in Terminology and Phrasing Alter Search Results?
6.2 Unimaginable Communities

7.0 How Search Results Change Throughout Time: 2015, 2017, 2021
7.1 Longitudinal Overview: Official Languages in Each Domain
7.2 Terminology Throughout Time: “Homosexual” vs. “Gay”
6.3 Phrasing Throughout Time: “Good” vs. “Wrong”

Conclusion

Chapter Five:
The Real Cost of Search Engines: Digital Advertising, Linguistic Capitalism, and the Rise of Fake News

Introduction

1.0 The Economics of Google

2.0 The Context of Post-Fordism

3.0 AdWords: Organic vs. Sponsored Results
3.1 AdWords: The Multilingual Linguistic Market and an Economy of Bias
3.2 Google’s Institutionalisation, Data-Collection, and Advertising
3.3 AdWords in the Context of “The Magic System”
3.4 AdWords and the General Intellect

4.0 The Economic Profits of Discrimination

5.0 Private Profits and Public Loses
5.1 Google’s International Expansion

6.0 AdSense and Post-Fordism: The Cost of Google’s Billboards
6.1 AdSense and Fake News in the 2016 US Presidential Election
6.2 The Reciprocal Relationship Between AdSense and Facebook

Conclusion


Conclusion: What if Search Engines Were Actually Built to Benefit Users?