This repository contains tools and datasets about search engine geography by Andrea Ballatore and colleagues.
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. Analyzing 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 these 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.
Search engines make information about places available to billions of users, who explore geographic information for a variety of purposes. The aggregated, large-scale search behavioural statistics provided by Google Trends can provide new knowledge about the spatial and temporal variation in interest in places. Such search data can provide useful knowledge for tourism management, especially in relation to the current crisis of tourist (over)crowding, capturing intense spatial concentrations of interest. Taking the Amsterdam metropolitan area as a case study and Google Trends as a data source, this article studies the spatial and temporal variation in interest in places at multiple scales, from 2007 to 2017. First, we analyze the global interest in the Netherlands and Amsterdam, comparing it with hotel visit data. Second, we compare interest in municipalities, and observe changes within the same municipalities. This interdisciplinary study shows how search data can trace new geographies between the interest origin (what place users search from) and the interest destination (what place users search for), with potential applications to tourism management and cognate disciplines.
Keywords: Internet geography, search engines, Google, localness, digital place
google_localness: data from a study on the localness of search results.
google_trends/google_trends_comparator: an R tool to compare 5+ search terms in Google Trends.
google_trends/google_trends_geographies: geographic studies based on Google Trends data.
- A. Ballatore, S. Scheider, & B. Spierings (2019) Tracing tourism geographies with Google Trends: A Dutch case study. In: Kyriakidis, P., Hadjimitsis, D., Skarlatos, D. & Mansourian, A. (eds.), AGILE Conference on Geographical Information Science: Geospatial technologies for local and regional development. Berlin: Springer.
- A. Ballatore, S. Scheider, & R. Lemmens (2018) Patterns of consumption and connectedness in GIS Web sources, AGILE Conference on Geographical Information Science: Geospatial Technologies for All, Lund, Sweden.
- A. Ballatore, M. Graham, S. Sen (2017) Digital Hegemonies: The localness of search engine results, Annals of the American Association of Geographers.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.