We are going to conduct a content analysis as outlined by Rose <?biblio ADDIN paperpile_citation <clusterId>A751N811J291H812</clusterId><version>0.6.12</version><metadata><citation><id>557b5e78-6b39-4940-ace9-af470183556e</id><no_author>true</no_author><prefix/><suffix/><locator>5</locator><locator_label>chapter</locator_label></citation></metadata> /* MERGEFORMAT?>(2016: ch. 5), and used in previous work <?biblio ADDIN paperpile_citation <clusterId>O343V491R781O574</clusterId><version>0.6.12</version><metadata><citation><id>faa9512f-6859-4ff4-a510-dd1881bd9eea</id><no_author/><prefix>e. g.</prefix><suffix/><locator/><locator_label>page</locator_label></citation><citation><id>acad2880-3e7a-448f-98b9-fc15c034a9f4</id><no_author/><prefix/><suffix/><locator/><locator_label>page</locator_label></citation></metadata> /* MERGEFORMAT?>(e. g. Bainotti et al., 2020; Towner and Muñoz, 2020): The first step is going to be an initial open coding of the collected images by the authors, supported by codes from the literature. Inspired by Bainotti et al. coding will focus on the content as in “what does the image show”, as well as the composition, as in “which Instagram specific affordances were used” (e.g. polls, questions, countdown, gif, …). Further narrative style and context of use are added. Coding of stories by members of the public will be the most challenging, as our approach means we must rely on our crowd supporters’ annotations using predefined codes. They will be evaluated by coding predefined public profiles. Data analysis will start in early 2022.