Turkish Sentiment Analysis for Open and Distance Education Systems

Autor/inn/en	Ergul Aydin, Zeliha; Kamisli Ozturk, Zehra; Erzurum Cicek, Zeynep Idil
Titel	Turkish Sentiment Analysis for Open and Distance Education Systems
Quelle	In: Turkish Online Journal of Distance Education, 22 (2021) 3, S.124-138, Artikel 8 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Ergul Aydin, Zeliha) ORCID (Kamisli Ozturk, Zehra) ORCID (Erzurum Cicek, Zeynep Idil)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1302-6488
Schlagwörter	Foreign Countries; Student Attitudes; Open Education; Distance Education; Telecommunications; Social Media; Educational Technology; Technology Uses in Education; Research Methodology; Classification; Turkey + Suchen Sie Ihr Suchwort? Ausland; Schülerverhalten; Offene Erziehung; Offener Unterricht; Distance study; Distance learning; Fernunterricht; Telekommunikationstechnik; Soziale Medien; Unterrichtsmedien; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Research method; Forschungsmethode; Classification system; Klassifikation; Klassifikationssystem; Türkei
Abstract	Students' opinions are the most essential source to enhance the quality of education and educational services in Open and Distance education (ODE) Systems. How to access and analyze students' real opinions is a problem for ODE institutions. The purpose of the present study is to conduct a sentiment analysis (SA) on the collected Turkish tweets about an ODE system to monitor students' opinions and sentiments about the system. Firstly, the related 63699 tweets about the ODE system are gathered and analyzed. Later, preprocessing is applied to the dataset. Sentence-based SA is performed with the data provided. The dataset is vectorized using two vector space models to test four classifiers which are Support Vector Machines, K-Nearest Neighbor, Logistic Regression (LR), and Artificial Neural Networks. F-score values obtained with these classifiers are evaluated, and the results are discussed. LR classifier gives the best F-score values with %75 for each vector space model. Through the SA results, students' dissatisfaction, appreciation, and concerns will be learned quickly by the university administration to develop strategies that will increase the quality of education and educational services. (As Provided).
Anmerkungen	Anadolu University. Office of the Rector, Eskisehir, 26470, Turkey. Tel: +90-222-335-34-53; Fax: +90-222-335-34-86; e-mail: rektor@anadolu.edu.tr; e-mail: TOJDE@anadolu.edu.tr; Web site: http://tojde.anadolu.edu.tr/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01