@inproceedings{7fcbc050b4bd4a6cb4c383c5eb553bb6,
title = "CourseObservatory: Sentiment analysis of comments in course surveys",
abstract = "This article describes experiments with a tool, called CourseObservatory, that applies sentiment analysis to comments made by students during course surveys. The main objective is to provide course coordinators and teachers with relevant information about the courses students take based on their qualitative feedbacks. The experiments use a dataset that contains comments in Portuguese found in questionnaires filled out by students from mid-2005 to the first semester of 2018, with a total of nearly 170,000 comments, after a cleaning process that removes blank comments. The experiments show that comments made by students are influenced by the final status achieved (approved or failed), among other facts.",
keywords = "Data Visualisation, Educational Data Mining, Sentiment Analysis",
author = "Jim{\'e}nez, \{Hayd{\'e}e G.\} and Casanova, \{Marco A.\} and Nunes, \{Bernardo Pereira\} and Finamore, \{Anna Carolina\}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019 ; Conference date: 15-07-2019 Through 18-07-2019",
year = "2019",
month = jul,
doi = "10.1109/ICALT.2019.00053",
language = "English",
series = "Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "176--178",
editor = "Maiga Chang and Sampson, \{Demetrios G\} and Ronghuai Huang and Gomes, \{Alex Sandro\} and Nian-Shing Chen and Bittencourt, \{Ig Ibert\} and Kinshuk Kinshuk and Diego Dermeval and Bittencourt, \{Ibsen Mateus\}",
booktitle = "Proceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019",
address = "United States",
}