Melike Artar
Biographic Data
| ID | 804197 |
|---|---|
| NAME | Melike Artar |
| GIVEN NAMES | Melike |
| FAMILY NAME | Artar |
| SIGNATURE | ARTAR M |
| AFFILIATIONS | Gebze Technical University |
| ORCID | 0000-0001-7714-748X |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Analyzing nomophobia among TikTok users
This study aims to investigate the phenomenon of nomophobia (fear of being without a mobile phone) among TikTok users from various countries. The study analyzes a dataset of TikTok posts from December 2020 to December 2022, employing volume analysis, keyword and latent distribution analysis (LDA), and sentiment analysis. These methods are utilized to explore the dynamics and nuances of discussions related to nomophobia among a global user base Th…
Predicting academic performance of students with machine learning
This study investigates the effectiveness of machine learning and deep learning models for early prediction of student performance in higher education institutions. Using the Open University Learning Analytics (OULA) dataset, various models, including Decision Tree, Support Vector Machine, Neural Network, and Ensemble Model, were employed to predict student performance in three categories: Pass/Fail, Close to Fail, and Close to Pass. The Ensemble…
Teleworking Sentiments on X
This research focuses on the use of digital technologies and platforms to give a detailed evaluation of the potential and problems connected with teleworking during the COVID-19 period. We gained insights into the teleworking experience by using user-generated content (UGC) from “X” ( n = 216,485) and used data mining methods such as sentiment analysis, topic modeling, and textual analysis. Based on our research, we determined that there are a to…
Breaking the Silence
Women's reproductive health has historically been marginalized within professional environments, regarded as a personal matter rather than a collective institutional issue, and predominantly excluded from organizational policies. Notwithstanding the direct influence of biological phenomena such as menstruation, maternity, and menopause on women's occupational experiences, these subjects have frequently been rendered obscured or deemed inappropria…
The evolutıon of dıgıtal leadershıp
This research paper examines the evolution of digital leadership as portrayed in The New York Times articles from 2020 to 2022, addressing the growing complexities and strategic roles influenced by digital technologies. The study identifies critical issues in digital leadership, including ethical dilemmas, cybersecurity threats, and the digital divide, which pose significant challenges to effective digital governance and strategy implementation. …
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The evolutıon of dıgıtal leadershıp
This research paper examines the evolution of digital leadership as portrayed in The New York Times articles from 2020 to 2022, addressing the growing complexities and strategic roles influenced by digital technologies. The study identifies critical issues in digital leadership, including ethical dilemmas, cybersecurity threats, and the digital divide, which pose significant challenges to effective digital governance and strategy implementation. …
Analyzing nomophobia among TikTok users
This study aims to investigate the phenomenon of nomophobia (fear of being without a mobile phone) among TikTok users from various countries. The study analyzes a dataset of TikTok posts from December 2020 to December 2022, employing volume analysis, keyword and latent distribution analysis (LDA), and sentiment analysis. These methods are utilized to explore the dynamics and nuances of discussions related to nomophobia among a global user base Th…
Predicting academic performance of students with machine learning
This study investigates the effectiveness of machine learning and deep learning models for early prediction of student performance in higher education institutions. Using the Open University Learning Analytics (OULA) dataset, various models, including Decision Tree, Support Vector Machine, Neural Network, and Ensemble Model, were employed to predict student performance in three categories: Pass/Fail, Close to Fail, and Close to Pass. The Ensemble…
Teleworking Sentiments on X
This research focuses on the use of digital technologies and platforms to give a detailed evaluation of the potential and problems connected with teleworking during the COVID-19 period. We gained insights into the teleworking experience by using user-generated content (UGC) from “X” ( n = 216,485) and used data mining methods such as sentiment analysis, topic modeling, and textual analysis. Based on our research, we determined that there are a to…
Breaking the Silence
Women's reproductive health has historically been marginalized within professional environments, regarded as a personal matter rather than a collective institutional issue, and predominantly excluded from organizational policies. Notwithstanding the direct influence of biological phenomena such as menstruation, maternity, and menopause on women's occupational experiences, these subjects have frequently been rendered obscured or deemed inappropria…
Psychology (4 works) · Art (2 works) · Computer Science (2 works) · Digital era (2 works) · Sociology (2 works) · 2019-20 coronavirus outbreak (1 work) · Advanced Technologies in Various Fields (1 work) · Anxiety (1 work) · Artificial Intelligence (1 work) · Computer-assisted web interviewing (1 work)