Climate change is something that people are growing more concerned about. In conjunction with this, sustainability is becoming more important for Swedish consumers who shop online. Studies have also shown that it has become more common to shop second hand. A company that seeks to capitalize on this is Sellpy. The company describes itself as Sweden's largest e-commerce for second hand items. The purpose of this essay was to conduct a critical rhetoric analysis to investigate how the rhetoric works in Sellpy's communication on the web page “Vårt ansvar”. In addition the study aimed to investigate if there were underlying meanings in Sellpy's communication. To accomplish the purpose of the study the theoretical framework includes rhetorical theories, more particularly the rhetorical situation and the rhetorical disposition. The theoretical framework also includes the terms greenwashing and corporate social responsibility. These terms are used as tools to strengthen our reasoning and to helps us interpret why Sellpy's communication looks the way it does. The method used in this study is critical rhetoric analysis and includes the aspects disposition and situation. It aims to gather a deeper understanding of why a message is formatted as it is. The result showed that the text on the page "Vårt ansvar" largely follows the five parts included in the rhetorical disposition. The results also indicate that the rhetoric in Sellpy's communication is used to convince the audience that Sellpy is a reliable company with a good sustainability agenda that continuously strives for improvement through its sustainability work. Finally our results show that there is a primary underlying meaning in Sellpy's communication, namely that Sellpy wants to capitalize. In addition to this we interpret that there are also two secondary underlying meanings: the audience is good and does the environment and society a favour if they use Sellpy’s service and Sellpy is a reliable company that does good.

Capsule network (CapsNet) is a new and promising approach to computer vision. In the small amount of research published so far, it has shown to be good at generalizing complex objects and perform well even when the images are skewed or the objects are seen from unfamiliar viewpoints. This thesis further tests this ability of CapsNetby comparing it to convolutional networks (ConvNets) on the task to understand images of clothing in different rotational views. Even though the ConvNets have a higher classification accuracy than CapsNets, the results indicate that CapsNets are better at understanding the clothes when viewed in different rotational views. / Capsule network (CapsNet) är en ny typ av neuralt nätverk för datorseende, som framförallt presterar bra även då bilderna är förvrängda eller sedda från obekanta vinklar. Den här uppsatsen testar CapsNets förmåga att förstå klädesobjekt sedda ur olika synviklar genom att göra en jämförelse med ConvNets. Resultaten visar att, trots att ConvNets har en högre exakthet i sin klassificering, är CapsNets bättre på att förstå kläderna sedda från olika synvinklar.