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This study focuses on predicting the likelihood of a developer participating in the PostgreSQL mailing list. The research involves extracting mail, generating threads, and creating a model for prediction. It evaluates the performance of the prediction model and explores future work. The study analyzes the top participants, thread generation strategies, message and thread characteristics, and the impact of word reduction on model performance. Collaborations between top participants and discussions involving specific individuals like Tom Lane and Bruce Momjian are examined to understand engagement patterns on the mailing list.
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Predicting the likelihood of a developer participating in the PostgreSQL mailing list Walid Ibrahim, Nicolas Bettenburg, Emad Shihab and Ahmed Hassan Software Analysis and Intelligence Lab (SAIL) Queen’s University {walid, nicolas, emads, ahmed}@cs.queensu.ca
Abstract • Predict, who is going to reply to a message. • Procedure done. • Extract Mail. • Generate Thread. • Get the Top 10 Participant. • Create a Model for prediction. • Evaluate the performance of prediction model. • Future work • Coloration between the top 10 participant in the mailing list.
Mail Extraction Process Parsing MBOX
The thread starter The person replied to The social dimension Number of messages Parent Known Number of words in the thread The Prediction Model Message and Thread Characteristics Dimension Date and time of the message Year of the message Thread subject attribute The Topic and Language Dimension Thread body attribute
Effect of stepwise reduction of words on model performance. Number of words Number of words
Topics discussed between Tom Lane and Bruce Momjian in January 2001