Difference between revisions of "Extracting the Main Path of Historic Events from Wikipedia"
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| − | '''Extracting the Main Path of Historic Events from Wikipedia''' - scientific work related to Wikipedia quality published in 2017, written by Benjamin Cabrera and Barbara König. | + | '''Extracting the Main Path of Historic Events from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2017, written by [[Benjamin Cabrera]] and [[Barbara König]]. |
== Overview == | == Overview == | ||
| − | The large online encyclopedia | + | The large online encyclopedia “[[Wikipedia]]” has become a valuable information resource. However, its large size and the interconnectedness of its pages can make it easy to get lost in detail and difficult to gain a good overview of a topic. As a solution authors propose a procedure to extract, summarize, and visualize large [[categories]] of historic Wikipedia articles. At the heart of this procedure authors apply the method of main path analysis—originally developed for citation networks—to a modified network of linked Wikipedia articles. Beside the aggregation method itself, authors describe data mining process of the Wikipedia datasets and the considerations that guided the visualization of the article networks. Finally, authors present web app that allows to experiment with the procedure on an arbitrary Wikipedia category. |
Revision as of 07:41, 29 August 2019
Extracting the Main Path of Historic Events from Wikipedia - scientific work related to Wikipedia quality published in 2017, written by Benjamin Cabrera and Barbara König.
Overview
The large online encyclopedia “Wikipedia” has become a valuable information resource. However, its large size and the interconnectedness of its pages can make it easy to get lost in detail and difficult to gain a good overview of a topic. As a solution authors propose a procedure to extract, summarize, and visualize large categories of historic Wikipedia articles. At the heart of this procedure authors apply the method of main path analysis—originally developed for citation networks—to a modified network of linked Wikipedia articles. Beside the aggregation method itself, authors describe data mining process of the Wikipedia datasets and the considerations that guided the visualization of the article networks. Finally, authors present web app that allows to experiment with the procedure on an arbitrary Wikipedia category.
