Emotion detection of social data: APIs comparative study.

The development of emotion detection technology has emerged as an efficient possibility in the corporate sector due to the nearly limitless uses of this new discipline, particularly with the unceasing propagation of social data. In recent years, the electronic marketplace has witnessed the establishment of various start-up businesses with an almost sole focus on building new commercial and open-source tools and APIs for emotion detection and recognition. Yet, these tools and APIs must be continuously reviewed and evaluated, and their performances should be reported and discussed. There is a lack of research to empirically compare current emotion detection technologies in terms of the results obtained from each model using the same textual dataset. Also, there is a lack of comparative studies that apply benchmark comparisons to social data. This study compares eight technologies: IBM Watson Natural Language Understanding, ParallelDots, Symanto - Ekman, Crystalfeel, Text to Emotion, Senpy, Textprobe, and Natural Language Processing Cloud. The comparison was undertaken using two different datasets. The emotions from the chosen datasets were then derived using the incorporated APIs. The performance of these APIs was assessed using the aggregated scores they delivered and the theoretically proven evaluation metrics such as the micro-average of accuracy, classification error, precision, recall, and f1-score. Lastly, the assessment of these APIs incorporating the evaluation measures is reported and discussed.

Awareness of electronic crimes related to E-learning among students at the University of Jordan.

The spread of e-learning as an alternative to traditional or face-to-face education has faced many problems and challenges in general and ethical and legal challenges in particular. This study aims to measure students' awareness of the safe use of technology and its tools in e-learning that is consistent with ethical and legal standards. The study attempts to reveal the degree of awareness of students of the University of Jordan about electronic crimes related to e-learning and the legal procedures and penalties related to electronic crimes in e-learning. Quantitative research methods were used. A questionnaire was established and distributed to students enrolled in the following online courses: Ethics and Human Values, Communication Skills, and National Culture. Analysis of the data revealed that students had a high awareness about cybercrime due to the widespread use of the internet by students as it became an integral part of their daily lives. The degree of awareness of student about legal procedures and penalties related to electronic crimes in e-learning was medium. This indicates students' lack of awareness of the effectiveness of procedures and penalties for electronic crimes that can be applied in e-learning due to the rapid transition in the learning process at the University of Jordan from traditional learning to distance e-learning that was imposed during the Corona pandemic. Based on these findings, the study presented a set of recommendations that could be implemented to increase awareness and maximize the benefit of using e-learning.