Volume 6, Issue 4 (3-2020)
Human Information Interaction 2020, 6(4): 42-49 |
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Babaee M, Rastegarpour H. Opinion Mining, Social Networks, Higher Education. Human Information Interaction 2020; 6 (4)
URL: http://hii.khu.ac.ir/article-1-2871-en.html
URL: http://hii.khu.ac.ir/article-1-2871-en.html
Kharazmi University
Abstract: (2550 Views)
Background and Aim: With the advent of technology and the use of social networks such as Instagram, Facebook, blogs, forums, and many other platforms, interactions of learners with one another and their lecturers have become progressively relaxed. This has led to the accumulation of large quantities of data and information about students' attitudes, learning experiences, opinions, and feelings about the teaching-learning process. Opinion mining is one of the growing applications of data mining knowledge which by discovering patterns and models in users' opinions could help higher education to well plan, make well-versed policies, and to have fruitful management. Therefore, the purpose is to describe the applications of opinion mining to advance the excellence of higher education in Iran.
Methodology: Research method is an applied qualitative one. Population comprises of all the research and books associated with opinion mining that were available in reputable databases of IEEE, SSCI, Elsevier, CIVILICA, and Science Direct during the research data collection period in the spring of 2019. Using the convenience sampling method, 35 articles were selected with the aim of reviewing and describing educational opinion mining and analyzing its application in higher education.
Results: Based on the studies, it was found that opinion mining can be used as an effective tool in three parts: 1. Improving student performance; 2. Designing better online courses; and 3. Evaluating the efficiency of the educational activities of universities, professors, and various programs. Therefore it can also help to recognize the existing shortcomings, strengths, and weaknesses.
Conclusion: Higher education can scrutinize the sentiments, opinions, and ideas generated by students through opinion mining. Exploring this valuable information enables educational institutions, principals, and educators to make more appropriate decisions in education and improve the quality of educational services which leads to the improvement of academic performance and better career choices for individuals.
Methodology: Research method is an applied qualitative one. Population comprises of all the research and books associated with opinion mining that were available in reputable databases of IEEE, SSCI, Elsevier, CIVILICA, and Science Direct during the research data collection period in the spring of 2019. Using the convenience sampling method, 35 articles were selected with the aim of reviewing and describing educational opinion mining and analyzing its application in higher education.
Results: Based on the studies, it was found that opinion mining can be used as an effective tool in three parts: 1. Improving student performance; 2. Designing better online courses; and 3. Evaluating the efficiency of the educational activities of universities, professors, and various programs. Therefore it can also help to recognize the existing shortcomings, strengths, and weaknesses.
Conclusion: Higher education can scrutinize the sentiments, opinions, and ideas generated by students through opinion mining. Exploring this valuable information enables educational institutions, principals, and educators to make more appropriate decisions in education and improve the quality of educational services which leads to the improvement of academic performance and better career choices for individuals.
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