We present an interactive Web platform that, given a directed graph, allows identifying the most relevant nodes related to a given query node. Besides well-established algorithms such as PageRank and Personalized PageRank, the demo includes Cyclerank, a novel algorithm that addresses some of their limitations by leveraging cyclic paths to compute personalized relevance scores. Our demo design enables two use cases: (a) algorithm comparison, comparing the results obtained with different algorithms, and (b) dataset comparison, for exploring and gaining insights into a dataset and comparing it with others. We provide 50 pre-loaded datasets from Wikipedia, Twitter, and Amazon and seven algorithms. Users can upload new datasets, and new algorithms can be easily added. By showcasing efficient algorithms to compute relevance scores in directed graphs, our tool helps to uncover hidden relationships within the data, which makes of it a valuable addition to the repertoire of graph analysis algorithms.

In this paper we present the Wikipedia Diversity Observatory, a project aimed to increase diversity within Wikipedia language editions. The project includes dashboards with visualizations and tools which show the gaps in terms of concepts not represented or not shared across languages. The dashboards are built on datasets generated for each of the more than 300 language editions, with features that label each article according to different categories relevant to overall content diversity. Through various examples, we show how the tools encourage and help editors to bridge the gaps in Wikipedia content. Finally, we discuss the project's impact on the communities and implications for the Wikimedia movement, in a moment in which covering diversity is considered strategic.

Collaborative content creation inevitably reaches situations where different points of view lead to conflict. We focus on Wikipedia, the free encyclopedia anyone may edit, where disputes about content in controversial articles often reflect larger societal debates. While Wikipedia has a public edit history and discussion section for every article, the substance of these sections is difficult to phantom for Wikipedia users interested in the development of an article and in locating which topics were most controversial. In this paper we present Contropedia, a tool that augments Wikipedia articles and gives insight into the development of controversial topics. Contropedia uses an efficient language agnostic measure based on the edit history that focuses on wiki links to easily identify which topics within a Wikipedia article have been most controversial and when.

Collaborative content creation inevitably reaches situations where different points of view lead to conflict. In Wikipedia, one of the most prominent examples of collaboration online, conflict is mediated by both policy and software, and conflicts often reflect larger societal debates.