Hi, I am a first year masters students at Purdue University and would like to propose a project idea for GSoC 2017. I have worked on Vandalism Detection in Wikipedia in the past and understand how important it is to predict if an information is correct or not as it may be misleading to others.
Hence, I would like to propose this project idea: *Title: *Detect if a user edit made in OSM is a vandal edit or regular. *Summary: *It's a very challenging task to monitor the malicious edits or spams manually for a large active user base. I plan to identify the cases of vandalism on OSM by classifying edits as either regular or vandal. This is clearly a Binary Classification task, but if the distribution of regular and vandalism cases in the dataset are skewed, it can also be explored as an Anomaly Detection problem. *Requirements: *Lots of data about the edits made, information about the users making the edit, information about the people annotating the true labels, etc. I would appreciate if someone can provide a feedback on the project idea and the requirements needed. Thanks, Animesh Sinha
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