Yazar "Büyükeke, Ahmet" seçeneğine göre listele

Listeleniyor 1 - 6 / 6
  • [ X ]
    Öğe
    A text mining analysis of customer evaluations in terms of gastronomy tourism
    (2021) Büyükeke, Ahmet; Özsoy, Tufan
    Nutritional alternatives, which were limited to regional diversity in the past, have increased extraordinarily over time. Besides being the basic element to sustain life, it has come to the fore as hedonic consumption. It is already known that discovering the local cuisine and the pleasure of eating are very important for tourists. Social media platforms have become the most effective tool for tourists in making decisions. They significantly influence the decisions of tourists on where to go, where to stay, what to eat and drink. The primary aim of this research is to analyze and make sense of TripAdvisor reviews of restaurants serving Kaş and Belek, which have different accommodation alternatives. For this purpose, topic modelling, sentiment, and name-entity recognition analyses were carried out with 10,829 customer comments from 147 businesses. Reviews are clustered under the most appropriate 3 distinct subjects (Experience, Food, and Atmosphere). The satisfaction level in the comments is 89.52% for Kaş and 95.64% for Belek. In total, 800 and 445 different food names were discovered in Kaş and Belek reviews, respectively. Most liked foods: Meat dishes such as steak, burger, and stroganoff with cream, pepper, tomato, garlic, and spicy sauces.
  • [ X ]
    Öğe
    An Exploratory Case Study for Turkish Sentiment Classification Using Graph Convolutional Neural Networks
    (Institute of Electrical and Electronics Engineers Inc., 2021) Kiliç, Yasir; Büyükeke, Ahmet
    Graph Convolutional Neural Networks (GCNs) are highly popular in recent years. It gives very successful results for various natural language processing (NLP) tasks such as sentiment classification. It has recently been shown to be effective and successful models to solve sentiment classification problem of texts. However, there is no research demonstrating the performance of this model on Turkish texts. In this study, we observe performance of the GCN model on the sentiment classification problem of Turkish texts as first research. Since the structure of Turkish language is agglutinative, different preprocessing approaches are presented and performance results on three real-world Turkish sentiment datasets are shown . It is observed that the TripAdv dataset, which was used in this study, yielded a 0.76 F-measure value. This can be considered a reasonable success for a sentiment classification with three sentiment classes. On the other hand, this study is presented as an exploratory case study in preparation for more detailed and extensive research in the future. © 2021 IEEE
  • [ X ]
    Öğe
    An Inverse Approach to Windows' Resource-Based Permission Mechanism for Access Permission Vulnerability Detection
    (2022) Temiz, Hakan; Büyükeke, Ahmet
    In organizations, employees work with information stored in files according to their duties and responsibilities. Windows uses resource-based access permissions that any permission for any user has to be set separately per resource. This approach gets complicated as the number of resources and users increase, and causes oversights in assigning permissions. Therefore, a special mechanism is required to scrutinize what permissions any employee has on any set of resources. This requirement is circumvented by reversing the Windows’ approach in terms of user-accessible resources. This approach is implemented by a program allowing quick and easy examination of any type of permissions granted or denied to active directory users on any folder. In this way, administrators can make sure there is no any missing or overlooked setting that could cause a security vulnerability. This approach can easily be extended to scrutinize other resources, and for other local or active directory objects.
  • [ X ]
    Öğe
    Analysing perceptions towards electric cars using text mining and sentiment analysis: A case study of the newly introduced TOGG in Turkey
    (Henry Stewart Publications, 2022) Penpece Demirer, Dilek; Büyükeke, Ahmet
    The electric car market is growing steadily around the world and, accordingly, has become an attractive research area. It is important to understand the consumer perspective on newly introduced electric cars, such as those of Turkey’s Automobile Joint Venture Group Inc. (TOGG). Thus, the purpose of this study is to provide a better understanding of consumers’ perceptions related to the newly introduced TOGG, which may create a competitive advantage. Social media is an abundant source of textual data that allows for very reliable analysis and understanding of consumer opinions. In this study, Twitter comments on TOGG were collected and studied. Text mining, sentiment analysis and topic model analysis were then conducted. The results show that TOGG is a popular product with the public: there are many more positive Twitter comments related to TOGG than negative ones. The topics identified in social media are price expectancy, production facility, design and features. The most frequent topic for both positive and negative comments is price expectancy. © Henry Stewart Publications 2054-7544 (2022).
  • [ X ]
    Öğe
    Analysis of Consumer Reviews on Second Home Use: A Research on a Social Travel Platform
    (2022) Özsoy, Tufan; Büyükeke, Ahmet
    Second home tourism, which is not recognised as a part of tourism activities or its place in tourism is relatively insignificant, has started to gain importance today. The advantages of renting a second home include its proximity to the city’s tourist attractions, being in touch with the local culture, making you feel at home, not being tied to a single point, and offering many options at lower costs. Second home tourism, which appears as an alternative to organised tourism businesses, can quickly enter the potential accommodation inventory, mainly thanks to electronic platforms that support the sharing economy. When the literature is analysed, it is understood that there are very few studies examine second homes through the sharing economy. These studies deal with exchanging second homes for a certain period (house swap). The neglect of user views on utilising second homes represents a gap. In the study, second home with increasing online popularity was approached from a different perspective and benefited from social platform reviews. The research is aimed to analyse the consumer evaluations for second homes in different geographies. The data is customer reviews on social media of second homes in popular tourist destinations (Palma-Spain, Chania-Greece, and Fethiye-Turkey). It has been collected automatically from the social travel platform (TripAdvisor) with the help of a program developed in the Python programming language. The number of comments for Palma, Chania and Fethiye is 215, 951 and 693, respectively. To evaluate the comments, topic model analysis was used, and those were clustered under “value”, “experience”, and “location” titles. In addition, name-entity analysis was used to identify top products and services such as “food”, “room”, “pool”, “shop”, and “beaches”. The sentiment analysis was used to score the determined products or services. For Palma, “beautiful beach”, “local restaurant”, and “spacious room”; for Chania, “fresh eggs”, “clean water”, and “minute walk”; for Fethiye, “jeep safari”, “private pool” and “local restaurant” were the most prominent features. Findings indicate that second homes in similar destinations have parallel consumer review content. Also, factors that generate demand for second homes (being at home and being-feeling local) are included in the literature supported by findings.
  • [ X ]
    Öğe
    Metin Madenciliği ve Duygu Analizi Yöntemleri ile Sosyal Medya Verilerinden Rekabetçi Avantaj Elde Etme: Turizm Sektöründe Bir Araştırma
    (2020) Büyükeke, Ahmet; Sökmen, Alptekin; Gencer, Cevriye
    Kullanıcıların deneyim, görüş ve tavsiyelerini içeren sosyal medya verileri, seyahate yeniçıkacak olanların kararlarını etkileyen en önemli unsurlardandır. Bu nedenle, Türkiyeekonomisinde vazgeçilmez bir değere sahip olan turizm sektörü için geliştirilecek olanstratejilerde hem politika yapıcıların hem de otel işletmelerinin müşteri yorumlarını dikkatealmaları, uygun yöntemlerle analiz etmeleri ve anlamlandırmaları gerekmektedir. Bubilgiler ışığında gerçekleştirilen çalışmanın temel amacı, büyük sosyal medya verilerindengüncel metin madenciliği yöntemleriyle otel işletmeleri açısından rekabetçi bir zekâoluşturulmasıdır. Uygulama alanı olarak Antalya bölgesinin seçilmesinin temel sebebi hemtemel bir cazibe merkezi olması, hem de Türkiye'nin turizm başkenti olarak kabuledilmesidir. Veriler, Tripadvisor platformundan crawler geliştirilerek otomatik olaraktoplanmıştır. Toplam yorum sayısı 212,435’tir. Duygu Analizi için; Lojistik Regresyon,Destek Vektör Makinesi ve Naive Bayes kullanılmıştır. Analiz sonucunda yorumlarının%80’inin olumlu, %20’sinin olumsuz olduğu bulunmuştur. Konu analizi sonucunda;Deneyim %26,70 ile birinci, Değer ve Eğlence %24,68 ile ikinci, Şikâyet %20,41 ile üçüncüsırada yer almaktadır. Diğer konular; %16,15 ile Temel Hizmetler ve %12,06 ile YapılacakŞeyler’dir.