Abstract
AbstractIn this paper, we present the development of an opinion‐mining module. The development of the module consisted of creating an emotion tagged dataset of opinions; implementing an opinion mining module that processes sentences about computer programming, predicting or recognizing their polarity (positive/negative) and their type of emotion (frustrated, bored, excited, engagement, and neutral); and integrating the previous module in an intelligent learning environment. We evaluated the corpus, the accuracy of text polarity, and emotion recognition. The results with respect to polarity are promising (88.26%), however, the results in the detection of emotions are still low (60.0%). The reasons which likely explain these outcomes include a relatively small (7,777 records) and unbalanced corpus.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
