Predicting the price of second-hand vehicles using data mining techniques

The electronic commerce, known as “E-commerce”, has been boosted rapidly in recent years, and makes it possible to record all information such as price, location, customer’s review, search history, discount options, competitor’s price, and so on. Accessing to such rich source of data, companies can analyze their users’ behavior to improve the customer satisfaction as well as the revenue. This study aims to estimate the price of used light vehicles in a commercial website, Divar, which is a popular website in Iran for trading second-handed goods. At first, highlighted features were extracted from the description column using the three methods of Bag of Words (BOW), Latent Dirichlet Allocation (LDA), and Hierarchical Dirichlet Process (HDP). Second, a multiple linear regression model was fit to predict the product price based on its attributes and the highlighted features. The accuracy index of Actuals-Predictions Correlation, the min-max index, and MAPE methods were used to validate the proposed methods. Results showed that the BOW model is the best model with an Adjusted R-square of 0.7841

Author-Topic Modeling of DESIDOC Journal of Library and Information Technology (2008-2017), India

This study presents a method to analyze textual data and applying it to the field of Library and Information Science. This paper subsumes a special case of Latent Dirichlet Allocation and Author-Topic models where each article has one unique author and each author has one unique topic. Topic Modeling Toolkit is used to perform the author-topic modeling. The study further which considers topics and their changes over time by taking into account both the word co-occurrence pattern and time. 393 full-text articles were downloaded from DESIDOC Journal of Library and Information Technology and were analyzed accordingly. 16 core topics have been identified throughout the period of ten years. These core topics can be considered as the core area of research in the journal from 2008 to 2017. This paper further identifies top five authors associated with the representative articles for each studied year. These authors can be treated as the subject-experts for the modeled topics as indicated. The results of the study can serve as a platform to determine the research trend; core areas of research; and the subject-experts related to those core areas in the field the Library and Information Science in India

Understanding consumers’ emotions and sensory experience for beauty care products

Doctor of PhilosophyDepartment of Food, Nutrition, Dietetics and HealthMartin TalaveraUnderstanding consumer experience related to hedonic, sensory, and emotional aspects of products is the key to driving consumer-centric product design for the beauty care category. This dissertation conducted three independent studies aiming to explore consumer experience of beauty care products from two perspectives: liking and beyond liking (emotions), based on conventional sensory and consumer data and online product reviews. The objective of Chapter 2 was to develop an emotion lexicon that could be used to profile consumers’ emotional responses to beauty care products in sensory and consumer tests. The lexicon was developed in four main steps: sourcing terms from online product reviews, term identification and categorization, term refinement, and term validation. The final emotion lexicon consists of 37 positive emotions and 2 negative emotions. Recommendations on the application of this lexicon to each of the three categories of beauty care (skincare, hair care and makeup) were provided. The validated emotion lexicon from this study is readily applicable to other emotion research for skincare, hair care and makeup. Chapter 3 explored sensory drivers of liking and emotional associations for beauty care products. Hand creams were used as testing samples to be evaluated for sensory characteristics and consumer perception. First, the sensory space (aroma, appearance, texture & skinfeel) of twelve hand creams was profiled by a highly trained descriptive panel using a modified flavor/texture profile approach. Then, seven hand creams selected from the descriptive sensory space were rated for overall liking, emotions using the lexicon developed from Chapter 2, and consumer characterization using check-all-that-apply (CATA) in a home use test (HUT) with a hundred female consumers from the Kansas City area. Cluster analysis and external preference mapping identified three consumer clusters with different liking patterns: the thick & waxy-texture likers, mild scent & low-medium-thickness likers, and strong-scent likers. Consumers with different liking patterns differed in their emotional associations with sensory characteristics of hand creams. However, high intensities of certain aroma attributes seemed to elicit high-arousal emotions for all groups. The findings of this study could guide the development of new hand cream products targeting different consumer segments. Chapter 4 explored consumer experience for hand cream products from the “voice of consumers”-online product reviews. A total of 17, 581 reviews representing 46 hand creams of different brands, price points, and sensory attributes were collected from Amazon and Ulta Beauty using a scraping software. Topic modeling using Latent Dirichlet allocation (LDA) identified five major topics consumers mentioned in these online reviews: greasiness & residue of the product, scent/fragrances of the product, skin feel & efficacy of the product, consumers’ skin issues, and occasions when to apply the product. Term frequency–inverse document frequency (tf-idf) calculated for each rating group suggested that unpleasant scent and overall dissatisfied quality were the main reasons why consumers gave a rating lower than 4 stars. High efficacy and desirable skinfeel were the drivers for 5 stars. These findings highlighted the importance of sensory experience and perception of efficacy in consumers’ whole product experience

Elektronik ağızdan ağıza iletişimde ürün mü, satış hizmeti mi değerlendiriliyor? Karşılaştırmalı bir analiz

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.İnternet teknolojilerinin ve Web 2.0 platformlarının gelişmesi ile popüler bir iletişim aracı haline gelen elektronik ağızdan ağıza iletişim (e-Wom) birçok tüketici tarafından önemli bir bilgi kaynağı haline gelmiştir. E-Wom tüketicilerin bilgi arama, değerlendirme ve satın almada karar verme davranışlarında güçlü bir etkisi vardır. Tüketici yorumları, tüketicilerin kişisel deneyimlerine dayanarak internet üzerinde ürettikleri ürün bilgileridir ve e-Wom'un en yaygın biçimlerinden birini oluşturur. Günümüzde birçok e-ticaret platformu, tüketicilere satın aldıkları ürün veya hizmetler hakkında deneyimlerini paylaşabilmesi için yorum yapma ve yıldız derecelendirmesi imkanı sağlamaktadır. Çevrimiçi kullanıcılar, kendilerine sunulan çevrimiçi değerlendirmeleri aracılığıyla, diğer kullanıcıların görüşlerine göre satın alma kararlarını gerçekleştirirler. Bu çalışmanın amacı, tüketim mallarına yönelik yorumların ürüne mi, ürünün satışı için sunulan hizmete mi yönelik olduğu sorusuna yanıt aramaktır. E-ticaret siteleri üzerinde yapılan tüketici yorumları ve derecelendirmeleri, bazı ürün grupları için ürünün ötesine geçebilmekte ve ürün satışı için sağlanan hizmete yönelik yorumların ortaya çıkmasına neden olmaktadır. Bazı ürün grupları içinse doğrudan ürünün özelliklerine ve kalitesine yönelik yorumların ortaya çıkmasına neden olmaktadır. Araştırmada ürün yorumları ve yıldız derecelendirmelerini analiz etmek adına metin madenciliği analizlerinden yararlanılacaktır. Elde edilen veri seti, WordStat® yazılımı aracılığıyla analiz edilerek yorumlanacaktır. Elde edilen sonuçlar neticesinde; spesifik ürün gruplarına yapılan yorumlarda, ürün ve ürünün satışı için sunulan hizmetlere yönelik yorumların ayrıştırılması adına yorum yapılan platformların geliştirilmesine katkı sağlanacaktır. Bu çalışmanın elde ettiği sonuçlar ile literatüre spesifik ürün gruplarının yorum değerlendirmeleri bağlamında, pratiğe ise kategorik yorum ve değerlendirme önerileri ile katkıda bulunacağı öngörülmektedir.Electronic Word of Mouth (e-Wom), which has become a popular communication tool with the development of Internet technologies and Web 2.0 platforms, has become an important source of information by many consumers. E-Wom has a strong impact on consumers' search, evaluation and decision-making behavior. Consumer reviews are product information that they produce on the Internet based on personal experience of consumers and constitute one of the most common forms of e-Wom. Today, many e-commerce platforms provide reviews and star rating to enable consumers to share their experiences on the products or services they purchase. Online users make purchase decisions based on the opinions of other users through their online reviews. The purpose of this study is to answer the question of whether the comments about the consumer goods are related to the product or the service offered for the sale of the product. Consumer reviews and star ratings on e-commerce sites can go beyond the product for some product groups and lead to comments on the service provided for product sales. For some product groups, direct comments on the properties and quality of the product are produced. In this research, text mining analysis will be used to analyze product reviews and star ratings. The resulting data set will be analyzed by WordStat® software. According to the results obtained; in the comments made to specific product groups, contribution will be made to the development of platforms in order to differentiate comments on the services offered for the sale of products and products. It is foreseen that the results obtained from this study will contribute to the literature with the comments of the specific product groups and with the categorical interpretation and evaluation suggestions to the practice