Social media is a vast, fluctuant domain that is difficult to grasp, overlook and explain. It is important in our daily lives as well as for organisations, such as traditional media. Traditional media is moving from analogue news propagation to propagating news online, where social media plays a significant role. This study contributes to the understanding of traditional media propagation in social media, through quantitative and network analysis of articles’ spread in social media. The study also contributes to refining social media network analysis methodology, from the perspective of traditional media propagation in social media. The study is conducted as a survey where web documents of social media posts were collected and analysed. The scope of the study were Swedish traditional media. Two analysis methods were used: a quantitative statistical analysis of the propagation of articles and a network analysis comparing the usefulness of two common network analysis metrics: indegree centrality and PageRank. The results show that an overall of 22,34% of traditional media articles in this study, were propagated in social media. The findings include what categories of articles are most propagated on different social media platforms. Different kinds of newspapers were also compared, and variances were found. Local press articles were more propagated on Facebook than on Twitter, in opposite to national press that were more propagated on Twitter than on Facebook. Indegree centrality was found to be the most useful metric for examining traditional media propagation amongst Swedish newspapers, when compared to PageRank. Lack of cross-platform research in social media is pointed at, since this study identifies a prominent need for evolving cross-platform social media research.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:du-28178 |
| Date | January 2018 |
| Creators | Eriksson Asp, Tova |
| Publisher | Högskolan Dalarna, Informatik |
| 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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