This study aimed to examine how a company like Anamma creates a platform where people can connect and inspire others to buy vegan food and what strategies they use to do so. The empirical material consisted of eight posts on Instagram made by the Swedish vegan company Anamma. The posts are showing how vegan meals can be healthy, tasteful but also how it is good for the environment. Since the material in these posts were both text, pictures and animated videos a multimodal analysis was most suitable to get a valid and true result. Initially the posts were analyzed one by one. Then we summarized the result into three themes based on what was discovered during the first analysis. The study shows that Anamma is using strategic tools like the theory of Two-step-flow, or Word of mouth to make people hear about them. By using hashtags and tagging people they are creating a chain of equivalence, using the digital platform to spread their message. They also use words like, “together”, “all of us” and “save the planet” et cetera, which is assumed to make people want to be a part of making the world a better place. Also, they frequently use statistics as a strategy of persuasion to show how much less effluent vegan food is to the environment compared to meat. Using the word “Anamma-friends” is a strategy that helps create a strong community for their customers. All their strategies combined contributes to creating social identity and a feeling of belonging. However, this study is not a study of communication effects, since that would require a different approach. Therefore the conclusion of this study is that Anammas communication is effective and adequate towards the social context and can be seen as successful in relation to the purpose of the study.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-178992 |
Date | January 2020 |
Creators | Björkman, Patricia, Andersson, Heléne |
Publisher | Umeå universitet, Institutionen för kultur- och medievetenskaper |
Source Sets | DiVA Archive at Upsalla University |
Language | Swedish |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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