What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions
February 17, 2020 Β· Declared Dead Β· π The Web Conference
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Volodymyr Miz, JoΓ«lle Hanna, Nicolas Aspert, Benjamin Ricaud, Pierre Vandergheynst
arXiv ID
2002.06885
Category
cs.SI: Social & Info Networks
Cross-listed
cs.CY
Citations
19
Venue
The Web Conference
Last Checked
3 months ago
Abstract
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
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Social & Info Networks
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
node2vec: Scalable Feature Learning for Networks
R.I.P.
π»
Ghosted
Cooperative Game Theory Approaches for Network Partitioning
R.I.P.
π»
Ghosted
From Louvain to Leiden: guaranteeing well-connected communities
R.I.P.
π»
Ghosted
Fake News Detection on Social Media: A Data Mining Perspective
R.I.P.
π»
Ghosted
Heterogeneous Graph Attention Network
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Language Models are Few-Shot Learners
R.I.P.
π»
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
π»
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
π»
Ghosted