LİNKEDIN PROFİL ÖZELLİKLERİNİN ÇOK KRİTERLİ BİR YAKLAŞIM İLE DEĞERLENDİRİLMESİ VE BİR İŞE ALIM SÜRECİ VAKA İNCELEMESİ

Abstract

İş arayanlar veya işverenleri tek bir sosyal medya platformunda toplayan LinkedIn, kullanıcıların kendi oluşturdukları çevrimiçi bir profil aracılığıyla doğrudan karar vericilere ulaşmasına imkân sağlamaktadır. Günümüz iş piyasasında artan rekabet ortamı ve iş arayanların kendilerini rakiplerinden farklılaştırmalarının zorlaşması LinkedIn profillerinin ve profil özelliklerinin önemini artırmaktadır. Mevcut çalışmada aralık-değerli sezgisel bulanık (ADSB) kümeler ile VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) yönteminin birlikte kullanıldığı entegre bir yaklaşım önerilmiştir. Uygulamada alanlarında uzman dört işe alım profosyoneli, LinkedIn profillerindeki özelliklerin önem derecelerini belirlemiş ve iş arayan üç adayı profillerine göre değerlendirilmiştir. Sonuçlar LinkedIn profil özelliklerinin önem derecelerine göre iş tecrübeleri (0.155), özet (0.153), başlık (0.144), referans (0.136), fotoğraf (0.128), paylaşım (0.121), takip (0.096) ve bağlantı (0.065) biçiminde sıralandığını göstermektedir.

Keywords

• sosyal medya
• LinkedIn
• aralık-değerli sezgisel bulanık kümeler
• bulanık mantık
• VIKOR

EVALUATION OF LINKEDIN PROFILE FEATURES WITH A MULTI-CRITERIA APPROACH AND A RECRUITMENT PROCESS CASE STUDY

Abstract

Gathering job seekers or employers on a single social media platform, LinkedIn allows users to directly reach decision makers through an online profile they create. The increasing competitive environment in today's job market and the difficulty for job seekers to differentiate themselves from their competitors increase the importance of LinkedIn profiles and profile features. The presence of ambiguous, contradictory and subjective information in complex decision-making problems can cause uncertainty. In order to effectively model such decision problems and define uncertainties, fuzzy logic and heuristic fuzzy sets and interval-valued heuristic fuzzy (ADSB) sets, which are high-level extensions of fuzzy logic, are used. In the current study, an integrated approach is proposed in which ADSB clusters and VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method are used together. In practice, four recruitment professionals who are experts in their fields determined the importance levels of the features on their LinkedIn profiles, and three job seekers were evaluated according to their profiles. The results show that LinkedIn profile attributes are ranked in order of importance as work experience (0,155), summary (0,153), title (0,144), reference (0,136), photo (0,128), share (0,121), follow (0,096), and link (0,065).

Keywords

• Social media
• LinkedIn
• Interval-valued intuitionistic fuzzy sets
• Fuzzy logic
• VIKOR

References

1. Brooks, B. A. (2019). LinkedIn and your professional identity. Nurse Leader, 17(3), 173-175.
2. Cooper, B., & Naatus, M. K. (2014). LinkedIn as a learning tool in business education. American Journal of Business Education, 7(4), 299-306.
3. Büyüközkan, G., Göçer, F., & Feyzioğlu, O. (2018). Cloud computing technology selection based on interval-valued intuitionistic fuzzy MCDM methods. Soft Computing, 22(15), 5091-5114.
4. Deng, H., & Yeh, C. H. (2006). Simulation-based evaluation of defuzzification-based approaches to fuzzy multiattribute decision making. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 36(5), 968-977.
5. Edwards, C., Stoll, B., Faculak, N., & Karman, S. (2015). Social presence on LinkedIn: Perceived credibility and interpersonal attractiveness based on user profile picture. Online Journal of Communication and Media Technologies, 5(4), 102-115.
6. Guillory, J., & Hancock, J. T. (2012). The effect of Linkedin on deception in resumes. Cyberpsychology, Behavior, and Social Networking, 15(3), 135-140.
7. Koch, T., Gerber, C., & De Klerk, J. J. (2018). The impact of social media on recruitment: Are you LinkedIn?. SA Journal of Human Resource Management, 16(1), 1-14.
8. Land, S. F., & Muntinga, D. G. (2014, January). To Shave or Not to Shave?-How Beardedness in a Linkedin Profile Picture Influences Perceived Expertise and Job Interview Prospects. In HCI (18), 257-265.

9. Land, S. F., Willemsen, L. M., & Unkel, S. A. (2015, August). Are spectacles the female equivalent of beards for men? How wearing spectacles in a LinkedIn profile picture influences impressions of perceived credibility and job interview likelihood. In International conference on HCI in business, 175-184.
10. Ma'arif, A., & Wulandari, A. (2021, Ekim). Face shape-based physiognomy in LinkedIn profiles with cascade classifier and k-means clustering. In 2021 8th International Conference on Electrical Engineering, Computer Science and Informatics (EECSI). 347-353.
11. Ollington, N., Gibb, J., & Harcourt, M. (2013). Online social networks: An emergent recruiter tool for attracting and screening. Personnel Review. 42(3), 248-265.
12. Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455.
13. Park, J. H., Cho, H. J., & Kwun, Y. C. (2011). Extension of the VIKOR method for group decision making with interval-valued intuitionistic fuzzy information. Fuzzy Optimization and Decision Making, 10(3), 233-253.
14. Safko, L., & Brake, D.K. (2009). The social media bible: Tactics, tools, and strategies for business success. Skin & Allergy News. Hoboken, NJ: John Wiley & Sons.
15. Zide, J., Elman, B., & Shahani-Denning, C. (2014). LinkedIn and recruitment: How profiles differ across occupations. Employee Relations. 36(5), 583-604.
16. Tan, C., & Chen, X. (2013). Interval-valued intuitionistic fuzzy multicriteria group decision making based on VIKOR and Choquet integral. Journal of Applied Mathematics, 1-16.