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A model for the probabilistic function followed in Wikipedia edition is presented and compared with simulations and real data. It is argued that the probability to edit is proportional to the editors number of previous editions (preferential attachment), to the editors fitness and to an ageing factor. Using these simple ingredients, it is possible to reproduce the results obtained for Wikipedia edition dynamics for a collection of single pages as well as the averaged results. Using a stochastic process framework, a recursive equation was obtained for the average of the number of editions per editor that seems to describe the editing behaviour in Wikipedia.
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In this work, we are interested in the inner-cultural background shaping broad peoples preferences. Our interest is also to track this human footprint, as it has the tendency to disappear due to the nowadays globalization. Given that language is a social construction, it is part of the historical reservoir, shaping the cultural (and hence collective) identity, then helping the community to archive accumulated knowledge about its culture and identity. We assume that the collective interest of a language-speaking community to document their events, people and any feature important for them, by the online encyclopedia Wikipedia, can act as a footprint of the whole groups collective identity. The analysis of the languages preferences into categories among several languages, could have also applications into the field of Multilingual Natural Language Processing (MNLP). We, then, report results about the number of edits, editors, and pages into categories, displayed by the several languages. Results are shown by several angles, and some extra measures complement the analysis.
The production and consumption of information about Bitcoin and other digital-, or crypto-, currencies have grown together with their market capitalisation. However, a systematic investigation of the relationship between online attention and market dynamics, across multiple digital currencies, is still lacking. Here, we quantify the interplay between the attention towards digital currencies in Wikipedia and their market performance. We consider the entire edit history of currency-related pages, and their view history from July 2015. First, we quantify the evolution of the cryptocurrency presence in Wikipedia by analysing the editorial activity and the network of co-edited pages. We find that a small community of tightly connected editors is responsible for most of the production of information about cryptocurrencies in Wikipedia. Then, we show that a simple trading strategy informed by Wikipedia views performs better, in terms of returns on investment, than classic baseline strategies for most of the covered period. Our results contribute to the recent literature on the interplay between online information and investment markets, and we anticipate it will be of interest for researchers as well as investors.
A number of human activities exhibit a bursty pattern, namely periods of very high activity that are followed by rest periods. Records of this process generate time series of events whose inter-event times follow a probability distribution that displays a fat tail. The grounds for such phenomenon are not yet clearly understood. In the present work we use the freely available Wikipedias editing records to tackle this question by measuring the level of burstiness, as well as the memory effect of the editing tasks performed by different editors in different pages. Our main finding is that, even though the editing activity is conditioned by the circadian 24 hour cycle, the conditional probability of an activity of a given duration at a given time of the day is independent from the latter. This suggests that the human activity seems to be related to the high cost of starting an action as opposed to the much lower cost of continuing that action.
We perform an in-depth analysis on the inequality in 863 Wikimedia projects. We take the complete editing history of 267,304,095 Wikimedia items until 2016, which not only covers every language edition of Wikipedia, but also embraces the comple
This report summarizes the results of a short-term student research project focused on the usage of Swedish Wikipedia. It is trying to answer the following question: To what extent (and why) do people from non-English language communities use the English Wikipedia instead of the one in their local language? Article access time series and article edit time series from major Wikipedias including Swedish Wikipedia are analyzed with various tools.
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