Interactions of Cultures and Top People of Wikipedia from Ranking of 24 Language Editions

Abstract

Wikipedia is a huge global repository of human knowledge that can be leveraged to investigate interwinements between cultures. With this aim, we apply methods of Markov chains and Google matrix for the analysis of the hyperlink networks of 24 Wikipedia language editions, and rank all their articles by PageRank, 2DRank and CheiRank algorithms. Using automatic extraction of people names, we obtain the top 100 historical figures, for each edition and for each algorithm. We investigate their spatial, temporal, and gender distributions in dependence of their cultural origins. Our study demonstrates not only the existence of skewness with local figures, mainly recognized only in their own cultures, but also the existence of global historical figures appearing in a large number of editions. By determining the birth time and place of these persons, we perform an analysis of the evolution of such figures through 35 centuries of human history for each language, thus recovering interactions and entanglement of cultures over time. We also obtain the distributions of historical figures over world countries, highlighting geographical aspects of cross-cultural links. Considering historical figures who appear in multiple editions as interactions between cultures, we construct a network of cultures and identify the most influential cultures according to this network.

Wikipedia access and contribution: Language choice in multilingual communities . A case study

“…The fact that, as stated above, the English Wikipedia has more articles and these tend to be longer, and arguably because English is commonly perceived as a universal language, affects the perception of this particular edition as being the best both in terms of reliability and coverage of topics. Despite this preference for English, there is no indication in our results that this is due to perceiving the smaller language editions to be more likely biased, as suggested by some literature (Pfeil et al, 2006;Massa and Scrinzi, 2013;Eom et al, 2015), but it rather seems to be related to the extension and completion in the more widely used language.…”

“…For a variety of reasons, there are significant differences in coverage, approaches and even internal policies among the different editions, which impact on how one can participate in the writing of articles. Additionally, there are the possible biases, which have been identified in the literature as being more likely to occur in smaller language communities, as it is expected that they would have a smaller group of people involved in the curation process (Pfeil et al, 2006;Massa and Scrinzi, 2013;Eom et al, 2015).…”

Multi-cultural Wikipedia mining of geopolitics interactions leveraging reduced Google matrix analysis

“…As such, G qrnd represents indirect (hidden) links between the N r nodes appearing via the global network. We note that certain matrix elements of G qr can be negative, which is possible due to the negative terms in Q c = 1 − P c appearing in (13). The total weight of negative elements is however much smaller than W qr (at least 6 times smaller and even non-existing in ArWiki).…”

“…At present directed networks of real systems can be very large (about 4.2 million articles for the English Wikipedia edition in 2013 [13] or 3.5 billion web pages (called also nodes) for a publicly accessible web crawl that was gathered by the Common Crawl Foundation in 2012 [18]). For some studies, one might be interested only in the particular interactions between a very small subset of nodes compared to the full network size.…”

Analysis of world terror networks from the reduced Google matrix of Wikipedia

“…These codes had been developed in the frame of EC FET Open NADINE project (2012)(2013)(2014)(2015) [22] and used for Wikipedia (2013) data in [4]. This work was granted access to the HPC resources of CALMIP (Toulouse) under the allocation 2017-P0110.…”