How The Internet Search Engine Reshaped The World

This current article provides an analysis on the noteworthy impact search engines have on society since genesis, particularly placing attention on Google. The search engine as a touchstone of modern digital culture, encompasses the notion not everything is honourable considering apparent fundamental business and ethical issues; prevailing social and cultural transformations. Understanding historic, social and cognitive contexts search engines express, is of importance for everyday users. An amalgamation of these notions is analysed.

“Crawler Based Search Engine” (Sullivan, 2002)

Figure 1: Explanation of Search Engines. Image: Neil Patel. All Rights Reserved.


The search engines first job is to ‘crawl’ the web with ‘spiders’.

These are automated programs – better known as bots – that scour the network for any information fitting a user’s search. These metaphorical spiders will take note of every search and click, to learn more about who you are, what you do and who you connect with.

Sullivan (2002) posits 3 main features search engines comprise of:

  1. Web Crawling: Browsing the web in an automated and methodical manner.
  2. Indexing: This is the fastest form of search where pages are elaborately analysed by headings, titles and fields.
  3. Software: The final step where users query prompts the engine to return the most relevant information.


The Genesis of Search Engines

As file cabinets overflowed and libraries were the exclusive place of storing and retrieving information (Halavais,2013), the industrial revolution aided innovative ideas and concepts to advance new technological advancements to combat organising and distribution of growing information.

What started as a research project for two Stanford university students, the foundation for the world’s most powerful search engine of time “Google” was conceived. At inception, the dream turned to reality when the duo successfully created a system that crawled the internet determining which pages linked to other relative pages; allowing users to find information quickly, all merit to a search engine that excels (Seymore, 2011)

What began as a novel search engine is now inclusive of eight products all whom retain over 1 billion users respectively (Verge, 2019). Google alone receives over 3.5 billion search engine query’s per day (Kunz, 2019) supporting claims that no technology organisation is arguably more responsible for shaping the internet and modern life than Google.

Although there is a variety of search engines in the network ecosystem, users champion Google’s to search the repository of available human knowledge, consume media, communicate and manoeuvre through the endless vat of the internet. Google won the search engine race due to its ability to discover and record novel information whilst delivering the most accurate results, doing so faster than any other available engine.


Figure 2: Market Share of All Available Search Engines. Image: Jumpshot. All Rights Reserved.
Figure 2: Market Share of All Available Search Engines. Image: Jumpshot. All Rights Reserved.

Search Engines are NOT perfect

Economic Implications of Advertising by Controlling Algorithms.

The initial algorithm which personalised results to deliver accurate and relevant information to users in a liberal manner, fostered the trustworthy judgments of Google. As the digital sphere transformed, changes to the current algorithm skew results to prioritise advertisers, ultimately a change motivated by profit (Patel, 2019). Businesses appreciate the crunch of mind-numbing data volumes at lightning speed, where users are given exactly what they’re looking for when they want it; a blameless reason to why google is the most attractive space to reach targeted consumers. Subsequently, leading to Google’s advertising business pulling 78% of all search ad revenues.

Figure 3: Share of Current Digital Ad Market. Image: eMarketer. All Rights Reserved.
Figure 3: Share of Current Digital Ad Market. Image: eMarketer. All Rights Reserved.
“Search Engine Marketing” offers exponential assistances to enhance brand awareness visible from searched keywords; increasing website traffic which with the right number of clicks can optimise the site to potentially appear first in search results. However, Companies can pay for advertisements to appear first, regardless of user’s search. It is imperative to understand the first promoted result acquires a staggering 75% clickthrough (Lazer,2018).

In essence information monopolies alike to Google uphold the ability to prioritize search results through a variety of channels, such as promoting their own companies interests over smaller, less profitable advertising competitors or multinational corporation counterparts (Noble, 2018).Thus, ranking pages according to intrinsic authority is completely flawed as ranks are open for manipulation, which consequently saw the EU fining Google 1.7 Billion over ‘abusive’ ad strategies in 2019.

Figure 4: One of Many EU Antitrust Fines to Google. Image: Statista. All Rights Reserved
Figure 4: One of Many EU Antitrust Fines to Google. Image: Statista. All Rights Reserved


Filtered results promoted may not reflect accurate user interests

A pause for thought, for individuals who participate in utilising the world’s biggest search engine. Google has been forced to implement change in its algorithm that suggest both racist and sexist answers via the auto-complete function; fronting users with ideologically skewed results.

Suggestive autocompletion pre-empts users anticipated search desires to make for a speedy process helpful through suggesting. Drawing on individuals past data and generic search results to shape the algorithm, particularly championing the ‘majority rules’ concept. UK journalist Carole Cadwalladr exposed this issue demanding Google explain why search queries alike to “are women” and “are Jews”, were being automatically completed exhibiting problematic suggestions. Particularly, members of minority groups inclusive of race and sexuality, are subject to prejudice – by the majority culture searches deemed ‘popular’ and therefore ‘relevant’(Jarrett,2014).


Figure 5: Example of Search Engines Auto-complete Racism. Image: Wired. All Rights Reserved.
Figure 5: Example of Search Engines Auto-complete Racism. Image: Wired. All Rights Reserved. 

Quinn (2016) hypothesised the search engine was being “gamed” by activist groups pushing extreme agendas, by means of bots flooding the web with links – to alter search engines predicted queries. Each of the given searches represents Google’s algorithmic conceptualisations, encompassing an array of people and ideologies (Noble, 2018)Google estimates .25% of daily traffic has been returning offensive and misleading content. It is not only prejudice limited through autocomplete function but also via images. In terms of the search engine image function, “women” results see whiteness overrepresented, where people of colour; although not entirely absent, are majorly unrepresented  (Noble, 2018) It is important to question is this exclusively Google’s issue? Or, a wider societal issue brought to light by modern search engine technology?

The notable problem with pre-empting intentions as a function, may subconsciously bookmark ideas and shape users’ mindsets with results that might not have been the intended search. Google’s suggested racist and sexist results is simply a reflection of society’s own cultural prejudice in the digital age (Noble,2013)


Search Engines: Political Implications

In news, Google is scrubbing autocomplete feature queries on the current US 2020 presidential candidates and voting, preventing suggestions that may lead to bias or inaccurate results (Nayak, 2020). This instituted change came two months ahead of the November elections to combat foreign interference through search engines, after the preceding 2016 election meddling by Russian operatives.



The last few decades signature technology focused on digitalisation and its ability to transport communication via networks (Jarrett, 2014) As individuals of the digital age, it is important to note how Search Engines collect and distribute information. There are many myths surrounding the Internet, including its seemingly democratic nature comprising of top results recognised as most ‘popular’ and ‘true’.

The updated personalisation algorithm exploited by search engines has altered priorities in efforts to be more profitable, making the web ecosystem less than neutral with its manipulation, particularly through advertising.

On this basis, it is contended that racism and prejudice are embedded within Google’s dominated search engine; prevalent through autocomplete and image extensions. However, algorithms don’t have their own values, they’re bound by what they pick up from users searching. Battelle’s (2013) idea: measuring intentions through search engines are accurate; unlike surveys or public expressions, searching directly infers intent of user online.

The importance of understanding technology stems from considering both social and informative environments. Thus, Search engines may unveil deep rooted social problems.

Importantly there are a vast amount of benefits search engines provide with remarkably easy access to the world’s knowledge. Whilst there may not be a simple solution to increase trustworthiness, there is most definitely a simple lesson. Be sceptical and don’t simply take results – especially first page – generated by Google or another search engine as gospel.


Word Count: 1299



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How Google’s Search Engine Really Works (A Peek Under The Hood). (2020, January 23). Retrieved from


Jarrett, Kylie (2014) A Database of Intention. In Society of the Query Reader: Reflections on Web Search. Konig R and Rasch M (eds). Amsterdam: Institute of Networked Cultures. 16-29


Lapowsky, I. (n.d.). Google Autocomplete Still Has a Hitler Problem. Retrieved from


Noble, Safiya U. (2018) A society, searching. In Algorithms of Oppression: How search engines reinforce racism. New York: New York University. pp. 15-63


Quinn, K. (2016, December 08). Google forced to change ‘racist’, ‘sexist’ algorithm after being ‘gamed’ by Right. Retrieved from