WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 4Citation - Scopus: 5Beyond Visual Cues: Emotion Recognition in Images With Text-Aware Fusion(Elsevier, 2025-04) Sungur, Kerim Serdar; Bakal, GokhanSentiment analysis is a widely studied problem for understanding human emotions and potential outcomes. As it can be performed over textual data, working on visual data elements is also critically substantial to examining the current emotional status. In this effort, the aim is to investigate any potential enhancements in sentiment analysis predictions through visual instances by integrating textual data as additional knowledge reflecting the contextual information of the images. Thus, two separate models have been developed as image-processing and text-processing models in which both models were trained on distinct datasets comprising the same five human emotions. Following, the outputs of the individual models' last dense layers are combined to construct the hybrid multimodel empowered by visual and textual components. The fundamental focus is to evaluate the performance of the hybrid model in which the textual knowledge is concatenated with visual data. Essentially, the hybrid model achieved nearly a 3% F1-score improvement compared to the plain image classification model utilizing convolutional neural network architecture. In essence, this research underscores the potency of fusing textual context with visual information to refine sentiment analysis predictions. The findings not only emphasize the potential of a multi-modal approach but also spotlight a promising avenue for future advancements in emotion analysis and understanding.Article Citation - WoS: 4Citation - Scopus: 9Are We Ready for the New Normal in E-Business Education? Sentiment Analysis of Learners' Opinions on MOOCs(Russian State Vocational Pedagogical Univ, 2021-04-18) Derindag, O. F.; Cizmeci, B.Introduction. The new digital economy and its constantly evolving paradigm have completely transformed the model of doing business and the learning methods. MOOCs (massive-open-online-courses) and micro-credentials are the educations interfaces, have become an important teaching environment tool. Distance learning has become an indispensable alternative teaching method in updating and transferring classical education materials according to real-world settings, especially for learners in higher education. Aim. The current research is aimed to address the society's readiness and attitude direction to the concept of MOOCs and distance learning, highlighting its emergence and inevitability for educational institutions of all types in order to make a fundamental change in their curricula, especially in e-business courses, which are the most demanded training courses on MOOCs platforms. Methodology and research methods. In the study, the awareness and recognition of the online community on the MOOCs concept is examined. in this direction, Turkish people's perception and attitudes toward MOOCs have been addressed via sentiment analysis on Eksi Sozluk, the largest social communication and discussion platform in Turkey. Results. According to the sentiment analysis results, it has been determined that 52% of respondents have positive judgments on distance education and MOOCs, 29% of responses are neutral and 18% are negative. In general, distance education and MOOCs are perceived as a useful new education model by the Turkish people. Scientific novelty. This paper is the first sentiment analysis of learners' opinions on MOOCs and distance learning in Turkey. Considering the increasing awareness of MOOCs and the need for e-business education, as the most demanded type of MOOCs, this is the first study investigating the priority of these two phenomena within the context of COVID-19. Practical significance. It is thought that this study will contribute to the stakeholders in terms of showing how MOOCs and micro-credentials have a high potential to understanding trends in education especially in the new normal after the COVID-19 pandemic. The holistic education model of institutions has difficulty meeting the competitive nature and result-oriented approach of the e-business ecosystem. This market reality requires the institutions to offer more to-the-point and applied education solutions. In terms of e-business (e-commerce, digital marketing) education, the importance of MOOCs as a solution-focused on "how" rather than "what." has been comprehensively discussed in the paper.Article Citation - WoS: 16Citation - Scopus: 11An Empirical Study of Sentiment Analysis Utilizing Machine Learning and Deep Learning Algorithms(Springernature, 2023-12-09) Erkantarci, Betul; Bakal, GokhanAmong text-mining studies, one of the most studied topics is the text classification task applied in various domains, including medicine, social media, and academia. As a sub-problem in text classification, sentiment analysis has been widely investigated to classify often opinion-based textual elements. Specifically, user reviews and experiential feedback for products or services have been employed as fundamental data sources for sentiment analysis efforts. As a result of rapidly emerging technological advancements, social media platforms such as Twitter, Facebook, and Reddit, have become central opinion-sharing mediums since the early 2000s. In this sense, we build various machine-learning models to solve the sentiment analysis problem on the Reddit comments dataset in this work. The experimental models we constructed achieve F1 scores within intervals of 73-76%. Consequently, we present comparative performance scores obtained by traditional machine learning and deep learning models and discuss the results.Article Citation - WoS: 5Citation - Scopus: 5A Digital 'Smiley Analysis of the Appreciation for Tourist Amenities by Visitors to London(Springer, 2025-03-28) Kourtit, Karima; Nijkamp, Peter; Osth, John; Turk, UmutDigital wellbeing research is on a rising edge. It is also increasingly applied in the hospitality sector to measure the satisfaction of visitors (metaphorically called here 'smileys'); understanding and enhancing visitor satisfaction are pivotal for the success of tourism destinations. This study seeks to identify critical factors influencing the visitors' appreciation for London, a city renowned for its allure, by harnessing available user data from Airbnb listings and hotels, using online reviews, with a particular view to the spatial pattern of visitors' choices in corona times. Advanced statistical techniques, including sentiment analysis, digital text analysis, multilevel analysis, and geographically weighted regression, are employed to discover geographical patterns as well as statistical correlations between land use, density, geographic location, and visitor contentment. The findings reveal that proximity to parks, accessibility to public transportation, and the presence of natural amenities exert substantial influence on visitor satisfaction in London. Especially, the proximity to a park enhances visitor satisfaction, predominantly in western London. Efficient access to public transportation in central areas of the city positively impacts visitor contentment levels as well. Furthermore, the availability of and accessibility to natural attractions in the southern and southwest areas of London appear to elevate visitor satisfaction. These novel insights empower destination managers, policymakers, and tourism stakeholders to make informed decisions, formulate targeted strategies, and enhance visitor experiences in specific London locales. The research highlights the importance of considering location-specific factors and customizing approaches to optimize the visitor appreciations for a city. By understanding the complex dynamics between land use, density, location, and visitor satisfaction, stakeholders can foster sustainable tourism growth and create a more appealing environment for visitors.