Using Topic Models to Study Journalist-Audience Convergence and Divergence: The Case of Human Trafficking Coverage on British Online Newspapers
Description: Despite the accessibility of online news and availability of sophisticated methods for analyzing news content, no previous study has focused on the simultaneous examination of news coverage on human trafficking and audiences' interpretations of this coverage. In my research, I have examined both journalists' and commenters' topic choices in coverage and discussion of human trafficking from the online platforms of three British newspapers covering the period 2009–2015. I used latent semantic analysis (LSA) to identify emergent topics in my corpus of newspaper articles and readers' comments, and I then quantitatively investigated topic preferences to identify convergence and divergence on the topics discussed by journalists and their readers. I addressed my research questions in two distinctive studies. The first case study implemented topic modelling techniques and further quantitative analyses on article and comment paragraphs from The Guardian. The second extensive study included article and comment paragraphs from the online platforms of three British newspapers: The Guardian, The Times and the Daily Mail. The findings indicate that the theories of "agenda setting" and of "active audience" are not mutually exclusive, and the scope of explanation of each depends partly on the specific topic or subtopic that is analyzed. Taking into account further theoretical concepts related to agenda setting, four more additional research questions were addressed. Topic convergence and divergence was further identified when taking into account the newspapers' political orientation and the articles' and comments' year of publication.
Date: August 2016
Creator: Papadouka, Maria Eirini
Partner: UNT Libraries