Extreme right-wing violence has increased in recent years. Social media technologies and self-made media platforms have allowed extreme right-wing groups to create and push narratives online. These narratives have inspired others to act outside of the digital world and commit horrendous [GH1] attacks targeting minorities. These narratives are also published in a hybrid media system where audience-driven content is favored by social media, rather than objective and correct content. Therefore, it is important to understand the use of digital storytelling and social media technologies in a political context to push political views and stories online. This thesis studied how The Nordic Resistance Movement (NRM) uses digital storytelling strategies to build and push narratives on Twitter and self-made media platforms. This was conducted through a network and qualitative content analysis. 400 000 tweets were collected using Twitter’s API from 1/1-2022 to 31/3-2022. The outcome indicates that NRM dilutes its hateful narrative on Twitter but uses digital storytelling to evoke interest in the movement and combines it with influential hashtags according to the network analysis to force users onto self-made media platforms. This is when the narrative changes to the extreme. The study concludes that NRM uses social media in combination with its digital storytelling to attract users from traditional political spaces on Twitter through intriguing storytelling as part of an initiation process to attract new members and visitors to their self-made media platforms. Further research is suggested to be done on media ecology concerning self-made media platforms to gain further insight into how the platforms affect each other and the storytelling in the hybrid media system.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mau-53025 |
| Date | January 2022 |
| Creators | Hall, Gustaw |
| Publisher | Malmö universitet, Institutionen för datavetenskap och medieteknik (DVMT) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| 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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