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Article Citation - WoS: 6Citation - Scopus: 10Male and Female Differences in the Use of Social Media for Learning Purposes(Routledge Journals, Taylor & Francis Ltd, 2018) Akman, Ibrahim; Turhan, CigdemThis study aims to explore the differences between male and female users' behaviour with regard to acceptance of social media for learning in higher educational institutions. For this purpose, a survey was conducted and the least square regression analysis approach was utilised to investigate the relationships among the constructs in the research model for male and female users from a general and ethical perspective, focusing on the reliability, performance and awareness factors. The findings from the analysis reveal that a significant degree of diversity is present in the factors represented by general reliability', ethical reliability', ethical performance', ethical awareness' and ethical intention'.Article Citation - WoS: 27Citation - Scopus: 43User Acceptance of Social Learning Systems in Higher Education: an Application of the Extended Technology Acceptance Model(Routledge Journals, Taylor & Francis Ltd, 2017) Akman, Ibrahim; Turhan, CigdemThis study aims to explore the users' behaviour and acceptance of social media for learning in higher educational institutions with the help of the extended Technology Acceptance Model (TAM). TAM has been extended to investigate how ethical and security awareness of users affect the actual usage of social learning applications. For this purpose, a survey was conducted and the Structural Equation Model approach was utilised to investigate the direct and indirect causal relationships among the constructs in the research model. Interestingly, the findings from the analysis reveal that, except ease of use', TAM's core and external constructs are significant predictors of actual behaviour towards using social media for learning.Article Citation - WoS: 2Citation - Scopus: 3A Hybrid Approach for Semantic Image Annotation(Ieee-inst Electrical Electronics Engineers inc, 2021) Sezen, Arda; Turhan, Cigdem; Sengul, GokhanIn this study, a framework that generates natural language descriptions of images within a controlled environment is proposed. Previous work on neural networks mostly focused on choosing the right labels and/or increasing the number of related labels to depict an image. However, creating a textual description of an image is a completely different phenomenon, structurally, syntactically, and semantically. The proposed semantic image annotation framework presents a novel combination of deep learning models and aligned annotation results derived from the instances of the ontology classes to generate sentential descriptions of images. Our hybrid approach benefits from the unique combination of deep learning and semantic web technologies. We detect objects from unlabeled sports images using a deep learning model based on a residual network and a feature pyramid network, with the focal loss technique to obtain predictions with high probability. The proposed framework not only produces probabilistically labeled images, but also the contextual results obtained from a knowledge base exploiting the relationship between the objects. The framework's object detection and prediction performances are tested with two datasets where the first one includes individual instances of images containing everyday scenes of common objects and the second custom dataset contains sports images collected from the web. Moreover, a sample image set is created to obtain annotation result data by applying all framework layers. Experimental results show that the framework is effective in this controlled environment and can be used with other applications via web services within the supported sports domain.Article Citation - WoS: 8Citation - Scopus: 10Employability of It Graduates From the Industry's Perspective: a Case Study in Turkey(Springer, 2013) Turhan, Cigdem; Akman, IbrahimThe qualifications that constitute the employability and identity of graduates are viewed differently by the academic community and the industry. Currently, it is observed for Information Technologies (IT) sector that the demands of the industry are not always satisfied by the perceived standards of the graduates. To provide feedback to the corresponding departments, a survey regarding employer expectations and factors affecting these expectations has been conducted among a number of senior professionals and managers working in the IT sector in Turkey regarding this inconsistency. The employer expectations are considered in two empirical categories as competencies and adequacies. The multiple regression analysis technique has been used to analyze the survey data. Based on the analysis, recommendations are provided to IT departments as well as their students to better fulfill the demands of the industry.Article Citation - WoS: 13Citation - Scopus: 24A Combined Approach for Customer Profiling in Video on Demand Services Using Clustering and Association Rule Mining(Ieee-inst Electrical Electronics Engineers inc, 2020) Guney, Sinem; Peker, Serhat; Turhan, CigdemThe purpose of this paper is to propose a combined data mining approach for analyzing and profiling customers in video on demand (VoD) services. The proposed approach integrates clustering and association rule mining. For customer segmentation, the LRFMP model is employed alongside the k-means and Apriori algorithms to generate association rules between the identified customer groups and content genres. The applicability of the proposed approach is demonstrated on real-world data obtained from an Internet protocol television (IPTV) operator. In this way, four main customer groups are identified: "high consuming-valuable subscribers", "less consuming subscribers","less consuming-loyal subscribers" and "disloyal subscribers". In detail, for each group of customers, a different marketing strategy or action is proposed, mainly campaigns, special-day promotions, discounted materials, offering favorite content, etc. Further, genres preferred by these customer segments are extracted using the Apriori algorithm. The results obtained from this case study also show that the proposed approach provides an efficient tool to form different customer segments with specific content rental characteristics, and to generate useful association rules for these distinct groups. The proposed combined approach in this research would be beneficial for IPTV service providers to implement effective CRM and customer-based marketing strategies.Article Citation - WoS: 2Citation - Scopus: 4Online Collaborative Tool Usage for Review Meetings in Software Engineering Courses(Routledge Journals, Taylor & Francis Ltd, 2022) Turhan, Cigdem; Akman, Ibrahim; Hacaloglu, TunaThe instructors generally utilize conventional methods in teaching software engineering courses, where the students are provided theoretical knowledge based on text books or lecture notes. Usage of collaborative tools may be a solution to the problems of not practicing the depth of the components of the subject. This study proposes the usage of a collaborative tool, namely, Google Docs in a software engineering course based on predefined scenarios. The review meeting subject was selected for this purpose and students' reactions were assessed with a survey after the completion of the experiments. The survey data were analysed using least square regression method. The results have shown that efficiency, certainty, satisfaction, advantage, complexity, learnability, and intention are indicators of the adoption of the online collaborative tool.Article The Individual Readiness and Risk-Related Concerns of It Professionals for Blockchain Adoption(Elsevier, 2025) Turhan, Cigdem; Akman, IbrahimBlockchain has gained remarkable momentum since its introduction in 2008, drawing the attention of industries, individuals, and governments on a global scale. This technology has been studied in the literature, with a focus on technical aspects, application areas, and emerging research challenges. However, few studies address individuals' perceptions of and concerns with respect to blockchain adoption. This study aims to investigate the attributes affecting blockchain adoption intention. A sample of IT professionals was used for this purpose since they are expected to have earlier and greater awareness of new digital technologies. The perceptions of this group of users regarding attributes such as innovativeness, self-efficacy, social pressure, and awareness, as well as their perceptions of privacy, security, and complexity, were examined through a survey of 208 responses. The results indicate that among the individual attributes, personal innovativeness, awareness, and social pressure positively affect blockchain acceptance, whereas security and privacy concerns fuel the reluctance to adopt blockchain. The findings hopefully provide insight for developers and management of enterprises to ensure a smooth transition into blockchain and present evidence to forecast its future.
