Affective Sentiment and Emotional Analysis of Pull Request Comments on GitHub

Sentiment analysis;Emotional Analysis;Deep Learning;Machine Learning;Natural Language Processing;Distance Metric Learning

Rishi, Deepakadvisor:Hoey, Jesse ; affiliation1:Faculty of Mathematics ; Hoey, Jesse ;

University of Waterloo

关键词: Sentiment analysis;    Distance Metric Learning;    Master Thesis;    Natural Language Processing;    Machine Learning;    Deep Learning;    Emotional Analysis;   

Others  :  https://uwspace.uwaterloo.ca/bitstream/10012/12728/3/RISHI_DEEPAK.pdf

瑞士|英语

来源: UWSPACE Waterloo Institutional Repository

【 摘 要 】

Sentiment and emotional analysis on online collaborative software development forums can be very useful to gain important insights into the behaviors and personalities of the developers. Such information can later on be used to increase productivityof developers by making recommendations on how to behave best in order to get a task accomplished. However, due to the highly technical nature of the data present in online collaborative software development forums, mining sentiments and emotions becomes a very challenging task. In this work we present a new approach for mining sentiments and emotions from software development datasets using Interaction Process Analysis(IPA) labels andmachine learning. We also apply distance metric learning as a preprocessing step before training a feed forward neural network and report the precision, recall, F1 and accuracy.