Abstract
Günümüzün popüler kelimeleri siber güvenlik ve sosyal medyadır. Teknolojinin ilerlemesi ve internet kullanımının artmasıyla birlikte bu kavramlar daha çok ön plana çıkmakta ve bu konudaki araştırmalar genişlemektedir. Bu makale, siber güvenlik konusunu ve Twitter'de siber güvenlik konusunu ele alan farklı iş sektörlerindeki meslekleri ele almaktadır. Bu nedenle, Twitter'deki siber güvenlik kavramları ve ve bu kavramlara katkıda bulunan meslekler ayrı ayrı analiz edilmiştir. Böylece siber güvenliğe katkı sağlayan iş sektörleri farklı kavramlara göre çıkarılmaya çalışılmıştır. Ayrıca, siber güvenlik kavramlarına odaklanan iş sektörleri de analiz edilmiştir. Önerilen makale, Twitter'deki siber güvenlik kavramlarına K-araç kümeleme yönteminin uygulanmasını ve bu kavramlar hakkında tweet'ler gönderen iş uzmanlarını göstermektedir.
Keywords
References
- Amati, G., Angelini, S., Cruciani, A., Fusco, G., Gaudino, G., Pasquini, D., & Vocca, P. (2021). Topic Modeling by Community Detection Algorithms. OASIS 2021 - Proceedings of the 2021 Workshop on Open Challenges in Online Social Networks, 15–20. https://doi.org/10.1145/3472720.3483622
- Hassan, L., Nenadic, G., & Tully, M. P. (2021). A social media campaign (#datasaveslives) to promote the benefits of using health data for research purposes: Mixed methods analysis. Journal of Medical Internet Research, 23(2). https://doi.org/10.2196/16348
- Johns, E. (2021). Cyber Security Breaches Survey 2021: Statistical Release. Department for Digital, Culture, Media and Sport. https://assets.publishing.service.gov.uk
- Morissette, L., & Chartier, S. (2013). The k-means clustering technique: General considerations and implementation in Mathematica. Tutorials in Quantitative Methods for Psychology, 9(1), 15–24. https://doi.org/10.20982/tqmp.09.1.p015
- Seemma, P. S., S. Nandhini, and M. Sowmiya. (2018). Overview of Cyber Security. Ijarcce, 7(11), 125–128. https://doi.org/10.17148/ijarcce.2018.71127 (2018)
- Pande, J. (2017). Introduction to Cyber Security ( FCS ). http://uou.ac.in
- Sadasivuni, S. T., & Zhang, Y. (2020). Clustering Depressed and Anti-Depressed keywords Based on a Twitter Event of Srilanka Bomb Blasts using text mining methods. Proceedings - 2020 IEEE International Conference on Humanized Computing and Communication with Artificial Intelligence, HCCAI 2020, December 2014, 51–54. https://doi.org/10.1109/HCCAI49649.2020.00014
- Soares, F. B., & Recuero, R. (2021). Hashtag Wars: Political Disinformation and Discursive Struggles on Twitter Conversations During the 2018 Brazilian Presidential Campaign. Social Media and Society, 7(2). https://doi.org/10.1177/20563051211009073
- Yoshida, M., Sakaki, T., Kobayashi, T., & Toriumi, F. (2021). Japanese conservative messages propagate to moderate users better than their liberal counterparts on Twitter. Scientific Reports, 11(1), 1–9. https://doi.org/10.1038/s41598-021-98349-2
Abstract
Today's buzzwords are cyber-security and social media. With the advancement of technology and the increased usage of the internet, these concepts are becoming more prominent and research on this subject is expanding. This paper addresses the issue of cyber-security and which professions in different business sectors discuss the topic of cyber-security on Twitter. Therefore, cyber-security concepts and contributors on Twitter are analyzed separately. In that way, business sectors that contributes to cyber-security are tried to be deduced with respect to different concepts. In addition, focuses of business sectors on cyber-security concepts are analyzed. The proposed paper demonstrates the application of the K-means clustering method to cyber-security concepts on Twitter and experts who posted tweets about these concepts.
Keywords
References
- Amati, G., Angelini, S., Cruciani, A., Fusco, G., Gaudino, G., Pasquini, D., & Vocca, P. (2021). Topic Modeling by Community Detection Algorithms. OASIS 2021 - Proceedings of the 2021 Workshop on Open Challenges in Online Social Networks, 15–20. https://doi.org/10.1145/3472720.3483622
- Hassan, L., Nenadic, G., & Tully, M. P. (2021). A social media campaign (#datasaveslives) to promote the benefits of using health data for research purposes: Mixed methods analysis. Journal of Medical Internet Research, 23(2). https://doi.org/10.2196/16348
- Johns, E. (2021). Cyber Security Breaches Survey 2021: Statistical Release. Department for Digital, Culture, Media and Sport. https://assets.publishing.service.gov.uk
- Morissette, L., & Chartier, S. (2013). The k-means clustering technique: General considerations and implementation in Mathematica. Tutorials in Quantitative Methods for Psychology, 9(1), 15–24. https://doi.org/10.20982/tqmp.09.1.p015
- Seemma, P. S., S. Nandhini, and M. Sowmiya. (2018). Overview of Cyber Security. Ijarcce, 7(11), 125–128. https://doi.org/10.17148/ijarcce.2018.71127 (2018)
- Pande, J. (2017). Introduction to Cyber Security ( FCS ). http://uou.ac.in
- Sadasivuni, S. T., & Zhang, Y. (2020). Clustering Depressed and Anti-Depressed keywords Based on a Twitter Event of Srilanka Bomb Blasts using text mining methods. Proceedings - 2020 IEEE International Conference on Humanized Computing and Communication with Artificial Intelligence, HCCAI 2020, December 2014, 51–54. https://doi.org/10.1109/HCCAI49649.2020.00014
- Soares, F. B., & Recuero, R. (2021). Hashtag Wars: Political Disinformation and Discursive Struggles on Twitter Conversations During the 2018 Brazilian Presidential Campaign. Social Media and Society, 7(2). https://doi.org/10.1177/20563051211009073
- Yoshida, M., Sakaki, T., Kobayashi, T., & Toriumi, F. (2021). Japanese conservative messages propagate to moderate users better than their liberal counterparts on Twitter. Scientific Reports, 11(1), 1–9. https://doi.org/10.1038/s41598-021-98349-2
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Publication Date | March 31, 2022 |
| Published in Issue | Year 2022 |