Digital Hegemonies: The Localness of Search Engine Results

Abstract

Every day, billions of Internet users rely on search engines to find information about places to make decisions about tourism, shopping, and countless other economic activities. In an opaque process, search engines assemble digital content produced in a variety of locations around the world and make it available to large cohorts of consumers. Although these representations of place are increasingly important and consequential, little is known about their characteristics and possible biases. Analysing a corpus of Google search results generated for 188 capital cities, this article investigates the geographic dimension of search results, focusing on searches such as "Lagos" and "Rome" on different localized versions of the engine. This study answers the questions: To what degree is this city-related information locally produced and diverse? Which countries are producing their own representations and which are represented by others? Through a new indicator of localness of search results, we identify the factors that contribute to shape this uneven digital geography, combining several development indicators. The development of the publishing industry and scientific production appears as a fairly strong predictor of localness of results. This empirical knowledge will support efforts to curb the digital divide, promoting a more inclusive, democratic information society.

Auditing the Personalization and Composition of Politically-Related Search Engine Results Pages

“…While informative, the findings from these audits are limited due to their reliance on proxy-based or otherwise indirect data collection methodologies, a lack of controls for isolating personalization, or a focus on a subset of the components that appear in modern Google SERPs [5,32,36,43,45]. Furthermore, the measures that have been previously employed to quantify ranking similarity, like Jaccard index or edit distance, are limited in their ability to distinguish between ranking differences that occur towards the top of a ranked list and differences that occur towards the bottom.…”

“…More recently, researchers exploring localized versions of Google found that the extent to which a geographical region has developed publishing and scientific industries is strongly correlated with the locality of search results returned [5]. Another recent audit was conducted on the search engines of Google, Yahoo, and Bing during the 2016 US Congressional Elections [45].…”

“…To set p we first obtained CTR data from January 2017 and found that the first 13 ranks (the average number of components in our dataset) accounted for 80.4% of clicks [67]. We used this to find a p = 0.938 that attributed 80.4% of the weight of the RBO evaluation to the first 13 ranks 5 .…”

Placing Wikimapia: an exploratory analysis

“…It is important to bear in mind that this data refers to search behaviour, and not to actual data production and consumption on Wikimapia and OpenStreetMap. Additionally, Internet access and Google search engine use vary nationally, reaching widely different percentages of the population (Ballatore et al, 2017). While acknowledging the limitations and noise contained in the data, Google Trends has been successfully used to investigate economic and cultural behaviours at a large scale (Preis et al 2012;Choi & Varian, 2012;Stephens-Davidowitz, 2013).…”

“…Not enough data is available for Sub-Saharan Africa and Central Asia. Interestingly, this spatial divergence retraces the digital divide between the Global North of high-income countries and the Global South, with medium-and low-income countries(Ballatore et al, 2017).Several explanations can be advanced in this context. First, Wikimapia originated from Russia, and might have been able to produce data about Russia and neighbouring countries more effectively.…”