Analysis of online jobs postings with data and text mining methods: Example of information and communication sector

In recent years, the amount of data has been increasing rapidly with the rapid development of the internet and the use of web-based applications. It is possible to make the increasing data useful for the business world with the effective use of data and text mining methods. Data mining is the process of obtaining meaningful and useful information from large data structures with the help of various algorithms. Although text mining has been associated with data mining or seen as a sub-branch of data mining, it is essentially a separate discipline. Text mining is the process of processing and analysing all kinds of text-containing expressions with the help of various algorithms and revealing various information that will create added value as a result. Companies may create advantages for themselves in the competitive environment by using text and data mining applications. In this study, it has been aimed to reveal useful information for all employees, employers and educational institutions. To achieve this, online job postings belonging to the Information and Communication Sector have been analysed by using data and text mining methods and determinations have been made regarding the labour market. Data have been obtained from an online job posting site. The obtained data have been analysed by Random Forest Decision Tree Algorithm and Hidden Dirichlet Discrimination methods. As a result, job descriptions were created for the subjects obtained from the analyzes made using the qualifications in the job postings. These job descriptions are likely to appear in job postings in the near future. In addition, it is determined that sensitive skills such as persuasion, communication, motivation, leadership, responsibility, flexibility, decision-making and consistency are among the dominant subjects for the information and communication sector, where technical skills are extremely important.