The Analysis of Opinions About Teaching Profession on Twitter Through Text Mining

Abstract Billions of data in social media have provided a very influential platform for researchers to make research on data analysis. In the digital age, it has become essential for conducting an analysis of written things in social media in which the individuals express easily themselves without any pressure and for studying big data. It has been known that there are shared subjects on the education like almost every subject on the Twitter platform. Accordingly, it is often shared about many issues relating to education. The purpose of the present study is to analyze shared ideas on the ‘teaching’ profession through this program, which has become popular recently. It was observed that the shared tweets were often related to the current problems about education and Twitter was used as a platform by the individuals to explain their problems. It was a considerable finding that most of the tweets focused on contracted teaching, the positions of appointment, public personnel selection exam and the system of exams, issues about assignation, paid to teach and interview issues that there are a great number of reaction tweets against negative evaluation about vacations of teacher and particularly, against the situations just like damaging the sanctity the teaching profession and these tweets take place in the category the most retweeted. With this research, it is suggested to make analyses on social media platforms with other data mining techniques on the same subject or different subjects, to analyze the shares of institutions and to examine the sharing of the Ministry of National Education