Abstract
In a changing media environment that is now largely considered to be hybrid, social media is becoming an increasingly important tool for the creation and dissemination of news stories. This creates a new form of framing called networked framing where users can partake in the creation of narratives regarding different subjects. The specific subject on which this study is focused are refugees who, being a specifically vulnerable group, are particularly susceptible to how they are framed as it affects the manner in which they are treated in the receiving country. Taking an interpretivist perspective, this study analysis the central refugeerelated events extracted from a sample of 12,758,376 tweets fetched in the time period between January 2020 and April 2021. By analysing the tweets’ hashtags and text using network analysis and computational frame analysis, this study seeks to answer (I) which frames are most prevalent for each event, (II) which entities are considered to be central actors, and (III) how each entity is framed. The study finds differences in the framing of refugees and migrants, where the first is perceived through a humanitarian and settlement frame whereas the latter is comparatively more often associated with economic themes. Beyond that, differences between causerelated and consequencerelated events are observed. As the refugees get closer to receiving countries, frames increasingly revolve around consequences whereas at the sources of the refugee’s plight humanitarian and causerelated frames, such as violence, prevail.
Educations | MSc in Business Administration and Data Science, (Graduate Programme) Final Thesis |
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Language | English |
Publication date | 2021 |
Number of pages | 138 |
Supervisors | Raghava Rao Mukkamala |