Mapping bilateral information interests using the activity of Wikipedia editors

Abstract

We live in a global village where electronic communication has eliminated the geographical barriers of information exchange. The road is now open to worldwide convergence of information interests, shared values and understanding. Nevertheless, interests still vary between countries around the world. This raises important questions about what today's world map of information interests actually looks like and what factors cause the barriers of information exchange between countries. To quantitatively construct a world map of information interests, we devise a scalable statistical model that identifies countries with similar information interests and measures the countries' bilateral similarities. From the similarities we connect countries in a global network and find that countries can be mapped into 18 clusters with similar information interests. Through regression we find that language and religion best explain the strength of the bilateral ties and formation of clusters. Our findings provide a quantitative basis for further studies to better understand the complex interplay between shared interests and conflict on a global scale. The methodology can also be extended to track changes over time and capture important trends in global information exchange.

Linguistic neighbourhoods: explaining cultural borders on Wikipedia through multilingual co-editing activity

“…Our finding is in line with Huntington's thesis which argues that cultural and religious identities of people form the primary source of potential conflict in the post-Cold War era [65]. The studies of email and Twitter communication [66] and similarity in country information interests [42] also reveal the patterns that echo religious "fault lines".…”

“…Population attraction and geographical proximity are the uniting factors that have been extensively discussed in the literature, most relevantly in the context of mobile communication flows [67] and migration [68]. Similar to our results, several studies report gravity laws in online settings, including [69] and [42]. Not only choice of topics to edit, but also online trade in taste-dependent products is affected by distance.…”

“…Since z-scores are sums across many independent variables, their distribution can be approximated by the normal distribution, and the threshold for link significance in the right tail is t = 3.32 √ L, where L = 3,066,736 is the number of concepts. We create a link between a pair of languages i, j if the observed z-score, z ij , is above the threshold t [42].…”

“…We use the resulting z-scores to build a network of shared topical interests, where the edges are weighted by the similarity of interest, quantifies via z-scores. In summary, this approach allows for discovering significant language pairs of shared interest, accounting for editions of different sizes, and avoiding over-representing the large editions [42].…”

Towards a Digital Reflexive Sociology: Using Wikipedia's Biographical Repository as a Reflexive Tool

“…In recent years, information from Wikipedia has been used in various scientific disciplines, such as media studies, the geography of information, computer science, computational linguistics or social physics. It has been used to study social phenomena as diverse as the structure of relations between languages (Eom et al 2015;Ronen et al 2014;Ban, Perc, and Levnajić 2017), geopolitical instability (Apic, Betts, and Russell 2011) or the similarity of interests between countries (Karimi et al 2015). It has also been used to analyze historical processes, such as large demographic trends (Reznik and Shatalov 2016), birth-death migration trajectories (Schich et al 2014), movements of famous people during their lives (Menini et al 2017), or the influence of the media on collective memory (Jara-Figueroa, Yu, and Hidalgo 2019).…”