WikiPulse - A News-Portal Based on Wikipedia (original) (raw)
Related papers
Indexing and analyzing wikipedia's current events portal, the daily news summaries by the crowd
Proceedings of the 23rd International Conference on World Wide Web, 2014
Wikipedia's Current Events Portal (WCEP) is a special part of Wikipedia that focuses on daily summaries of news events. The WikiTimes project provides structured access to WCEP by extracting and indexing all its daily news events. In this paper we study this part of Wikipedia and take a closer look into its content and the community behind it. First, we provide descriptive analysis of the collected news events. Second, we compare between the news summaries created by the WCEP crowd and the ones created by professional journalists on the same topics. Finally, we analyze the revision logs of news events over the past 7 years in order to characterize the WCEP crowd and their activities. The results show that WCEP has reached a stable state in terms of the volume of contributions as well as the size of its crowd, which makes it an important source of news summaries for the public and the research community.
A History of Newswork on Wikipedia
Proc. WikiSym'13
Wikipedia's coverage of current events blurs the boundaries of what it means to be an encyclopedia. Drawing on Gieyrn's concept of ``boundary work'', this paper explores how Wiki\-pedia's response to the 9/11 attacks expanded the role of the encyclopedia to include newswork, excluded content like the 9/11 Memorial Wiki that became problematic following this expansion, and legitimized these changes through the adoption of news-related policies and routines like promoting "In the News" content on the homepage. However, a second case exploring WikiNews illustrates the pitfalls of misappropriating professional newswork norms as well as the challenges of sustaining online communities. These cases illuminate the social construction of new technologies as they confront the boundaries of traditional professional identities and also reveal how newswork is changing in response to new forms of organizing enabled by these technologies.
High Tempo Knowledge Collaboration in Wikipedia’s Coverage of Breaking News Events
2012
When major news breaks in our hyper-connected society, we increasingly turn to an encyclopedia for the latest information. Wikipedia's coverage of breaking news events attracts unique levels of attention; the articles with the most page views, edits, and contributors in any given month since 2003 are related to current events. Extant scholarship has made little effort to understand how online communities like Wikipedia are able to engage in high-tempo knowledge collaboration.
WikiTopics: What is Popular on Wikipedia and Why
2011
We establish a novel task in the spirit of news summarization and topic detection and tracking (TDT): daily determination of the topics newly popular with Wikipedia readers. Central to this effort is a new public dataset consisting of the hourly page view statistics of all Wikipedia articles over the last three years. We give baseline results for the tasks of: discovering individual pages of interest, clustering these pages into coherent topics, and extracting the most relevant summarizing sentence for the reader. When compared to human judgements, our system shows the viability of this task, and opens the door to a range of exciting future work.
structure and dynamics of Wikipedia's breaking news collaborations
Despite the fact that Wikipedia articles about current events are more popular and attract more contributions than typical articles, canonical studies of Wikipedia have only analyzed articles about pre-existing information. We expect the coauthoring of articles about breaking news incidents to exhibit high-tempo coordination dynamics which are not found in articles about historical events and information. Using 1.03 million revisions made by 158,384 users to 3,233 English Wikipedia articles about disasters, catastrophes, and conflicts since 1990, we construct "article trajectories" of editor interactions as they coauthor an article. Examining a subset of this corpus, our analysis demonstrates that articles about current events exhibit structures and dynamics distinct from those observed among articles about non-breaking events. These findings have implications for how collective intelligence systems can be leveraged to process and make sense of complex information.
We have developed an application called Wikipedia Live Monitor that monitors article edits on different language versions of Wikipedia-as they happen in realtime. Wikipedia articles in different languages are highly interlinked. For example, the English article "en:2013_Russian_meteor_event" on the topic of the February 15 meteoroid that exploded over the region of Chelyabinsk Oblast, Russia, is interlinked with "ru:Падение_метеорита_на_Урале_в_2013_году", the Russian article on the same topic. As we monitor multiple language versions of Wikipedia in parallel, we can exploit this fact to detect concurrent edit spikes of Wikipedia articles covering the same topics, both in only one, and in different languages. We treat such concurrent edit spikes as signals for potential breaking news events, whose plausibility we then check with full-text cross-language searches on multiple social networks. Unlike the reverse approach of monitoring social networks first, and potentially checking plausibility on Wikipedia second, the approach proposed in this paper has the advantage of being less prone to falsepositive alerts, while being equally sensitive to true-positive events, however, at only a fraction of the processing cost. A live demo of our application is available online at the URL http://wikipedia-irc.herokuapp.com/, the source code is available under the terms of the Apache 2.0 license at https://github.com/tomayac/wikipedia-irc.
Staying in the Loop: Structure and Dynamics of Wikipedia’s Breaking News Collaborations
Despite the fact that Wikipedia articles about current events are more popular and attract more contributions than typical articles, canonical studies of Wikipedia have only analyzed articles about pre-existing information. We expect the coauthoring of articles about breaking news incidents to exhibit high-tempo coordination dynamics which are not found in articles about historical events and information.
What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions
Companion Proceedings of the Web Conference 2020
In this work, we propose an automatic evaluation and comparison of the browsing behavior of Wikipedia readers that can be applied to any language editions of Wikipedia. As an example, we focus on English, French, and Russian languages during the last four months of 2018. The proposed method has three steps. Firstly, it extracts the most trending articles over a chosen period of time. Secondly, it performs a semi-supervised topic extraction and thirdly, it compares topics across languages. The automated processing works with the data that combines Wikipedia's graph of hyperlinks, pageview statistics and summaries of the pages. The results show that people share a common interest and curiosity for entertainment, e.g. movies, music, sports independently of their language. Differences appear in topics related to local events or about cultural particularities. Interactive visualizations showing clusters of trending pages in each language edition are available online https://wiki-insights.epfl.ch/wikitrends CCS CONCEPTS • Applied computing → Sociology; • Human-centered computing → Social content sharing; Social navigation; Wikis.
Islander: A Real-Time News Monitoring and Analysis System
2022
With thousands of news articles from hundreds of sources distributing and sharing everyday, news consumption and information acquisition have been increasingly difficult for readers. Additionally, the content of news articles are becoming catchy or even inciting to attract readership, harming the accuracy of news reporting. We present Islander, an online news analyzing system for online news. The system allows users to browse trending topics with articles from multiple sources and perspectives. We define several metrics as proxies to news quality, and develop algorithms for automatic estimation. The quality estimation results are delivered through a web interface to news readers for easy access to news and information 1