Data Science and Applications https://www.jdatasci.com/index.php/jdatasci <p><em><strong>Data Science and Applications (DataSCI)</strong> </em>is an international peer-reviewed (refereed) journal which publishes original and quality research articles in the field of Data Science and its applications. <em><strong>DataSCI</strong></em> is published twice per year online. The aim of the journal is to publish original scientific researches based on data analysis from both life and social sciences. <em><strong>DataSCI</strong></em> also provides a data-sharing platform that will bring together international researchers, professionals and academics. The <em><strong>DataSCI</strong> </em>magazine accepts articles written in English.</p> <p>Our journal covers all the studies based on data&nbsp; analysis from&nbsp;both&nbsp;lifeand&nbsp;social&nbsp;sciences.&nbsp;Your data-based works can also be accepted in areas not mentioned below.</p> <ul> <li class="show"><strong># scientific data mining, machine learning, and Big Data analytics</strong></li> <li class="show"><strong># scientific data management, network analysis, and knowledge discovery</strong></li> <li class="show"><strong>#&nbsp;scholarly communication and (semantic) publishing</strong></li> <li class="show"><strong>#&nbsp;research data publication, indexing, quality, and discovery</strong></li> <li class="show"><strong>#&nbsp;data wrangling, integration, and provenance of scientific data</strong></li> <li class="show"><strong>#&nbsp;trend analysis, prediction, and visualization of research topics</strong></li> <li class="show"><strong>#&nbsp;scalable computing, analysis, and learning for Data Science</strong></li> <li class="show"><strong>#&nbsp;scientific web services and executable workflows</strong></li> <li class="show"><strong>#&nbsp;scientific analytics, intelligence, and real time decision making</strong></li> <li class="show"><strong>#&nbsp;socio-technical systems</strong></li> <li class="show"><strong>#&nbsp;social impacts of Data Science</strong></li> </ul> Dr. Murat Gök en-US Data Science and Applications 2717-6649 Performing DISC Personal Inventory Analysis in Job Postings Using Artificial Intelligence Methods https://www.jdatasci.com/index.php/jdatasci/article/view/80 <p>One of the application fields of DISC self-evaluation analysis was introduced to predict people's performance and orientation in their working life. Each letter in the word DISC represents an essential personal characteristic, dividing the profiles of people in business life into four essential parts. In the current study, DISC analysis is conducted on job postings to match the person with the job posting. The current study was based on the analysis of 3 different datasets with job postings in English, Turkish and Romanian prepared by using web scraping methods and then labeled in accordance with DISC criteria. Several different machine learning algorithms have been performed on the DISC analysis outputs, and they reached the best results with accuracy values of around over 96% on the English dataset, around over 95% on the Turkish dataset, and around over 96% on the Romanian dataset, for both D, I, S, C models.</p> Alperen Sayar Ahmet Yıldız Tuna Çakar Dilara Şengünoğlu Seyit Ertuğrul ##submission.copyrightStatement## 2023-12-31 2023-12-31 6 2 5 12