Sentiment analysis of students' Facebook comments toward university announcements
5th International Conference on Networking, Information Systems and Security, NISS 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2297380
ABSTRACT
Students' opinions are among the critical indicators to evaluate the university teaching process. However, due to the absence of an official online system in most universities that provides a mechanism for obtaining students' opinions on several university announcements, most students use various social networks to express their feelings and provide their opinions toward these announcements. We present, through this paper, sentiment analysis of Facebook comments written in the Moroccan Arabic dialect. These comments reflect the opinions of students about university announcements during the COVID-19 pandemic, especially those related to teaching mode and ex-am planning. Then, the comments collected were cleaned, preprocessed, and manually classified into four categories, namely positive, neutral, negative, and bipolar. Further, data dimensionality reduction is applied using TF-IDF and Chi-square test. Finally, we evaluated the performance of three standard classifiers, i.e., Naïve Bayesian (NB), Support Vector Machines (SVM), and Random Forests (RF) using k-fold cross-validation. The results showed that the SVM-based classifier performs as well as the RF-based classifier regarding the classification's accuracy and F1-score, while the NB-based classifier lags behind them. © 2022 IEEE.
Facebook comments; Machine learning; Moroccan Arabic dialect; Sentiment analysis; Student opinions; University announcements; Forestry; Random forests; Social networking (online); Statistical tests; Students; Support vector machines; Arabic dialects; Facebook; Facebook comment; Machine-learning; Naive Bayesian; Student opinion; Support vectors machine; University announcement
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
5th International Conference on Networking, Information Systems and Security, NISS 2022
Year:
2022
Document Type:
Article
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