Using visual and linguistic framing to support sustainable decisions in an online store

Companies face several digital communication challenges when it comes to promoting green products or services. The framing effect, which refers to the presentation of information, can significantly influence decision-making in digital interfaces. This research explores the impact of information framing through text and visuals on purchase decisions for sustainable fashion products. An online evaluation study (𝑁 = 84) of an e-commerce environment was conducted. We found that visual framing significantly affected user product choices, supporting more sustainability decisions. In contrast, little evidence was found that supported the effectiveness of linguistic (i.e., message) framing on user product choices. We discuss implications on how product pages should be designed to encourage sustainable decision-making

Using visual and linguistic framing to support sustainable decisions in an online store

Companies face several digital communication challenges when it comes to promoting green products or services. The framing effect, which refers to the presentation of information, can significantly influence decision-making in digital interfaces. This research explores the impact of information framing through text and visuals on purchase decisions for sustainable fashion products. An online evaluation study (𝑁 = 84) of an e-commerce environment was conducted. We found that visual framing significantly affected user product choices, supporting more sustainability decisions. In contrast, little evidence was found that supported the effectiveness of linguistic (i.e., message) framing on user product choices. We discuss implications on how product pages should be designed to encourage sustainable decision-making

On the Extraction and Use of Arguments in Recommender Systems: A Case Study in the E-participation Domain

In this paper, we present ongoing work on the automatic extraction of arguments from textual content, and on the use of interconnected argument structures by recommender systems. Differently to the majority of existing argument mining methods –which only consider ‘premise’ and ‘claim’ as the components of an argument, and ‘support’ and ‘attack’ as the possible relations between argument components–, we propose an argumentation model based on a detailed taxonomy of argumentative relations. Moreover, we provide a lexicon of English and Spanish linguistic connectors categorized in our taxonomy. As a proof of concept, we apply a simple, yet effective method that makes use of the built taxonomy and lexicon to extract argument graphs from citizen proposals and debates of an e-participation platform. We then describe how the extracted graphs could be exploited to generate and explain argument-based recommendationsThis work was supported by the Spanish Ministry of Science and Innovation (PID2019-108965GB-I00

Semantics-Aware Autoencoder

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Öneri sistemleri ve E- ticarette öneri sistemlerinin kullanımı

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.Anahtar kelimeler: Öneri sistemleri, içerik bazlı öneri sistemleri, işbirlikçi öneri sistemleri, hibrit içerik sistemleri, e-ticaret. İnternet üzerinden alışveriş, artık hayatımızda alışveriş alışkanlıklarımızı büyük bir ölçüde değiştirdi ve değiştirmeye de devam ediyor. Günün her saatinde her kategoride ürüne ulaşmamız için ihtiyacımız olan sadece internetle birlikte bir bilgisayar, akıllı telefon veya bir tablet. Bu sayede, ihtiyaç duyduğumuz veya almayı düşündüğümüz herhangi bir ürün için farklı alternatiflere, farklı kalite ve fiyatlara ulaşmamız artık çok kolay. Yaşadığımız ülkenin hatta dünyanın herhangi bir noktasından kapımıza kadar ürünün teslimini sağlayabiliyoruz. Öneri sistemleri, alınması düşünülen ürünler için aynı veya benzer ürünleri önceden almış başka müşterilerin yorum, değerlendirme ve oylarının da yardımıyla alternatif seçenekler veya tamamlayıcı başka ürünler önererek yapılacak alışverişi çok kolaylaştırmaktadır. Bu sayede zamandan tasarruf edilmesi, ihtiyaca daha yakın ürünlerin incelenmesi sağlanmış olur.Keywords: Recommendation systems, content-based recommendation systems, collaborative recommendation systems, hybrid recommendation systems, e-commerce Online shopping has changed our shopping habits to a great extent now and continues to change. In order to reach a product in any categories at any time of the day, we just need to have a computer, a smartphone or a tablet which has Internet connection. Thus, it becomes easy to reach different alternatives, different quality and prices for any product that we need or want to buy. Thanks to Internet, we can deliver the product from any place of the world. Suggestion systems make shopping much easier for the products to be bought by offering alternative options or complementary products with the help of the comments, evaluations and votes of other customers who have already bought the same or similar products for the intended products. Therefore, they help save time and examine the products that are most needed