A series of data visualizations for a generative publication that can be published weekly without human intervention: the Wikipedia vandalism report.
Through the Wikipedia API
all modifications to all wikipedia articles were stored for automatic processing. An algorithm was created to determine if an edit was malicious or genuine.
Every week the algorithm ran over the data collected in the previous seven days to determine which articles suffered most from online "vandalism". Reflecting world-wide sentiments on subjects like the news and pop culture. Articles on the "Tea Party movement", "Dancing with the stars", "The Notorious B.I.G", "Fred Phelps" and Wikipedia's own "Administrator intervention agains vandalism" were top ranking vandalism targets.
The graph above shows 7 days of heavy modification on the Tea Party movement article
. Users are listed on the right, individual edits are represented on the left. The length of each bar represents the total length of the article after the edit has been applied.
Distribution of malicious (red) and regular edits (green) on an article about Ei-ichi Negishi
, a Japanese chemist. This graph was generated right after he won the 2010 Nobel Prize in Chemistry. Apparently reason for both positive and negative attention.