Evaluating the websites of academic departments through SEO criteria: a hesitant fuzzy linguistic MCDM approach

ÖZKAN B., ÖZCEYLAN E., KABAK M. , Dagdeviren M.

ARTIFICIAL INTELLIGENCE REVIEW, cilt.53, ss.875-905, 2020 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 53 Konu: 2
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1007/s10462-019-09681-z
  • Sayfa Sayıları: ss.875-905


Search Engine Optimization (SEO) is the process of managing web content in a manner that elevates page rankings in search engines. Among other sectors, academic world is one of the number-one categories for search based on the percentage of web traffic generated through search engine referrals. However, SEO includes a number of factors grouped into two as 'on page' and 'off page.' To obtain maximum benefit from SEO, relevant factors/criteria should be considered using multi-criteria decision making (MCDM) methods. The focus of this paper is to consider SEO criteria evaluation as a MCDM problem in which the criteria are in different priority levels and the criteria values take the form of hesitant fuzzy linguistic term sets to facilitate the elicitation of information in hesitate situations. A three-step solution approach is developed: (i) determination of 21 SEO criteria, such as page loading time, page size and meta-keyword (ii) prioritizing the criteria using hesitant fuzzy analytic hierarchy process, and (iii) ranking 70 Turkish websites of the industrial engineering departments using Technique for Order Preference by Similarity to Ideal Solution. The results show that trust flow and XML sitemap are the determinant criteria among others. Using the proposed method, web designers can approach SEO from weighted criteria perspective.