Approach to processing of data from social networks for detecting public opinion on quality of educational services

Хомоненко, А. Д.; Dashonok, V. L.; Ivanova, Kseniya; Kassymova, Dinara

doi:10.1109/scm.2017.7970707

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…The applications of opinion mining in the education field are generally focused on detecting student opinion to improve the quality of online or face‐to‐face teaching l and to capture the public opinions relating to education . Our study focuses on the application of opinion mining to educational guidance.…”

Section: Resultsmentioning

confidence: 99%

“…Their experimental results have indicated that opinion mining becomes more difficult and challenging when performed for e‐learning blogs. In , the authors proposed an approach to identify public opinion on the basis of large data extracted from social networks for Detecting Public Opinion On Quality of Educational Services. Although they substantiate indicators for assessing public opinion by assessing the quality of educational services, the discrepancy between the expected and obtained indicators was revealed.…”

Section: Background Knowledge and Related Workmentioning

confidence: 99%

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Educational guidance process integrating opinion mining

Lazib

Bouarab-Dahmani

Haddadi

2019

Comp Applic In Engineering

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Opinion mining is a fast-developing field of study with numerous applications.It raises economic and political interests, especially in decision-making processes. In this paper, we are interested in educational opinion mining. We propose an educational guidance process that aims to improve university orientation after the secondary school cycle. Unlike the ordinary orientation processes, our process integrates the opinions of pupil, parents, and teachers, collected periodically. These opinions are treated to sort out the studies' domains in a positive polarity order. An orientation score is then calculated based on these opinions, the student's aptitudes and the continuous evaluation marks to guide pupils toward the most favourable discipline. The experimentations conducted on a sample of pupils (300) give a better convergence to the pupils' explicit choices using our proposal with a κ coefficient of 0.71, against 0.29 using only marks. K E Y W O R D Seducational guidance, opinion mining, opinion mining for education, opinion synthesis, pupil's opinions

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Section: Resultsmentioning

confidence: 99%

Section: Background Knowledge and Related Workmentioning

confidence: 99%