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

Öz

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.

Anahtar Kelimeler

• 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

Öz

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).

Anahtar Kelimeler

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

Kaynakça

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