Searching for Answers
Information Management, Search Engines, and the Information Ecology
Search engines seem to be pretty innocuous. Your interaction with them is brief and you probably pay it very little attention. In fact, most people when referring to the activity refer to one particular search engine: Google.
“I’ll Google it!”, “Just Google it” or “Did you Google it?” all refer to searching for information on the Web. This is significant when you realise that there are many other options out there.
This is only the beginning of our concerns, as the user interface is only one of the three steps involved in search and must be analysed to understand the process. Yikes!
Throughout this paper I will deconstruct the workings of the search engine to reach a deeper understanding of the information search engines provide and the impact search engines have on the shared imaginings of the world we live in.
I’ll start by situating search in it’s historical context and demonstrate the information management trends its evolution reflects. We’ll see how information management and search has evolved from responding to needs to creating needs for inquirers.
We’ll briefly explore the innerworkings of search engines in order to dissect the logic and theory behind search. This will inform us about what to expect from the information we find and why it is worth thinking critically about the information that is produced.
This will lead us to scrutinise how Google has benefited as the major search engine and how its ads based profit scheme has lead to bring about various business benefits, yet lead to potential damage of the information ecology and reinforced current flows of information and power excluding the marginalised.
History of Search
Before diving into history, what is a search engine?
Halavais (2013) defines a search engine as: “an information retrieval system that allows for keyword search of distributed digital text” (pp. 5-6). Essentially, I’m going to argue that search engines are gateways to the internet as information management systems. This necessary manipulation of information requires us to cast a critical eye the information it retrieves as it has the control to prioritise and demote information. If users want the best information, they must understand the driving forces that constitute search.
Search finds its history in information management and therefore is linked to the earliest form of information compilation. The most obvious example of this is the library, although some academics suggest that cave art may be technically characterised as one of these conceptually stretching the timeline even further back (Halavais, 2013).
It has always been based on the problem of too much information. Once a database outgrows in size the required efficiency for its use a system needs to be implemented to make it accessible (Halavais, 2013).
The first mechanical computer could be considered to have been created by Charles Babbage in 1823 when the British Government required a full record and calculation of tide tables for the ports. With algorithms, this information was made quickly accessible and searchable (Halavais, 2013).
With the invention of the World Wide Web, this same problem was presented but on a much larger scale. Not only was there too much content, but it was also difficult to map and categorise due to its content being created by users.
Various attempts were made to catalogue and index based on librarian and file clerk techniques:
- Archie: downloaded the directory listings of all the files located on public anonymous FTP (File Transfer Protocol) sites, creating a searchable database of file names – 1990.
- Gopher: a program designed for distributing, searching and receiving files over the internet – 1991.
- Veronica: keyword search of most Gopher menu titles.
- Jughead: tool for obtaining menu information from specific Gopher servers.
- W3Catalog: first primitive search engine – 1993.
- (Seymour, Frantsvorg & Kumar, 2011)
Neverthless, it was Google who succeeded above and beyond Yahoo and other early search engines due to its unique PageRank algorithms which listed pages based on relevance. Let’s dissect these innerworkings.
Mechanics of Search
Getting into the nuts and bolts of search algorithms might seem like exploring irrelevant programming or too technical to engage with. But it can be conceptually broken down to highlight its economic and social impact as is briefly outlined in Code.org’s video below. For a quick overview, take a look, but the critical analysis will be developed below.
The WorldWideWeb, as was briefly explained above, is a large number of interconnected pages through hyperlinks. These hyperlinks are what Google found to be the key in unlocking successful search.
PageRank is probably the most commonly discussed element of Google. The way Google decided to list pages in response to a search query was drawing on the opinion and validation of users recognised through hyperlinks. The more pages that link to a page, the greater preference it will be in Google’s results because a community interest has been identified in that page.
It is important to understand that Google’s algorithm is more complicated than this principal factor, including location and search history amongst others. Other search engines have tried other principles to relevancy such as Yahoo’s smaller scope and category based search.
However, relevance proved to be the most efficient and gave Google the edge they needed to get ahead. The competition between search engines has continued to drive innovation and further technological advance including pre-empting search through cookies and other methods of personalisation.
Impact of Search on the Information Ecology
The amount of may be surprising, but what is even more surprising is the principal source of revenue for search engines. For Google it’s advertising: 88.7% of the $77 billion dollars Google made in 2016. The two contributors were AdWords and AdSense (Graham, 2017).
AdWords essentially auctions advertising space on the search engine for particular searches. This leads to the commodification of words (Graham, 2017).
What is meant by this? Words potentially searched for gain an economic value through the bidding process. An interesting example is copyright name may actually be “bought” for advertising space and not legal action has been taken to prevent it.
This process runs the risk of constraining language that adapts to search. Users of search engines begin to adapt their phrases and formulations to suit the search engine consequently channelling people towards certain pre-empted results based on personalised information such as location, history and other metadata (Introna & Nissenbaum, 2000).
Not only this but, Google is beginning to rely further on sponsored pages to increase relevance for searches. More publicity to those who pay more is a direct contravention of the basic principles the internet was founded upon and which allowed various theorists to dream of an anarchist’s paradise.
Google, however, has incrementally stepped closer and closer towards reinforcing already existing flows of information and power. This has been demonstrated above in what has been coined as the reification of digital language (Graham, 2017).
Another example, however, involves the stereotypes and ideas that Google prioritises through the feedback loop of the users. Because the search engine draws on collective knowledge to inform its searches it begins to mirror society more and more closely.
Minority groups suffer as a result, with prejudiced autocompletions towards those of darker skin tone, alternative sexual orientation and even Semitic heritage to name a few examples (Paul Baker, 2013) These are reflections of the inherent flaws of the users of the search engine.
Screenshot from: Paul Baker, A. P. (2013). ‘Why Do White People Have Thin Lips?’ Google and the Perpetuation of Stereotypes via Auto-Complete Search Forms. Critical Discourse Studies, 10(2).
All this points to a deterioration in the information ecology of the World Wide Web (Lewandowski, 2008). New ideas and sources become repressed for the mainstream which sells. That is, at least for those who in their ignorance fail to dig deeper with their searches.
It is for these reasons that alternative search engines are beginning to find niche markets. DuckDuckGo is a prime example of a search engine responding to the amount of data that Google collates to pre-empt searches. DuckDuckGo offers greater privacy and potentially a more diverse and unbiased search due to its discount of search history. But is this potentially a trade off for efficiency and speed? All this must be evaluated when choosing a search engine.
What to make of it all…
Search engines are clearly powerful tools. Search engines are gatekeepers. A critical understanding of their innerworkings reveal that they control and manipulate as much as they provide and facilitate.
Google has the power to benefit and reinforce current information flows through PageRank, AdWords and other mechanisms it uses to provide users with results.
This is not to write off search engines. Indeed, even the Chinese search engine Baidu is extremely useful. But we must begin to approach our searches in a similarly critical fashion to the way would Baidu. Identifying the motives, mechanisms and influences behind the engine that will contribute to the results it provides me with.
It may also be an opportunity to consider alternatives to Google and include as part of the search process a conscious choice as to the engine you will entrust your data and your answers to.
It is also important to remember the Information Ecology of the web is still out there to be fostered and to flourish, but we must be aware that our search habits contribute to its cultivation. Let’s step out of the naivety of “Googling it” and take hold of our active roles as users. Let’s search.
Code.org. (2017, June 13).The Internet: How Search Works. Retrieved 12/10/2018 from https://www.youtube.com/watch?v=LVV_93mBfSU
Graham, R. (2017). Google and Advertising: Digital Capitalism in the Context of Post-Fordism, the Reification of Language and the rise of Fake News. Palgrave Communications, 3(1), 1-20. doi: 10.1057/s41599-017-0021-4
Halavais, A. (2013). The engines. In Search engine society (pp. 5–31). Cambridge, UK ; Malden, MA: Polity.
Introna, D., & Nissenbaum, H. (2000). Shaping the Web: Why the Politics of Search Engines Matters. The Information Society, 16(3), 169-185. doi: 10.1080/01972240050133634
Konig, R., & Rasch, M. (2014). A database of intention. In Society of the query reader: Reflections on web search (pp. 16–29). Institute of networked cultures.
Lewandowksi, D. (2008). Search Engine User Behaviour: How Can Users Be Guided to Quality Content? Information Services & Use, 28(3/4), 261-268. doi: 10.3233/ISU-2008-0583
Paul Baker, A. P. (2013). ‘Why Do White People Have Thin Lips?’ Google and the Perpetuation of Stereotypes via Auto-Complete Search Forms. Critical Discourse Studies, 10(2).
Seymour, T., Frantsvog, D., & Kumar, S. (2011). History of Search Engines. International Journal of Management and Information Systems, 15(4)
Hunt, E. (2106, December 18). What is fake news? How to Spot it and What You Can Do to Stop it. The Guardian. Retrieved from https://www.theguardian.com/media/2016/dec/18/what-is-fake-news-pizzagate