Mailing list repositories contain valuable information about the history of a project. Research is starting to mine this information to support developers and maintainers of long-lived software projects. However, such information exists as unstructured data that needs special processing before it can be studied. In this paper, we identify several challenges that arise when using off-the-shelf techniques for processing mailing list data. Our study highlights the importance of proper processing of mailing list data to ensure accurate research results.
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