Suchergebnisse

The phenomenon of so-called foreign fighters has in recent years attracted renewed public interest regarding why young people who have grown up in Western, democratic countries come to accept and engage in politically motivated violence, and these issues have received extensive news attention. Based on analysis of news texts published in four major Norwegian news outlets throughout 2014 and 2015, and supplemented with in-depth interviews with reporters, the present article investigates how radicalization and violent extremism are framed in the news, including how news conventions contribute to shape the ways in which these issues are defined in public debate. The analysis shows that authority definitions prevailed. 'Radicalized' individuals were predominantly presented as threats and criminals to be dealt with in the judicial system. A 'marginalization approach' was, however, also present in the reporting. This was partly due to reporters' efforts to bring personalized human-interest stories, which, to some extent, served to broaden the overall range of depictions. Simultaneously, issues pertaining to radicalization were mainly discussed at micro- and mesolevels, and more abstract political or systemic explanations not actualized by specific events or easily concretized through foregrounding specific individuals were largely absent. The article contributes new insights into characteristics of public discourses of radicalization and violent extremism, and how these are constructed in the intersection between news conventions and (elite) sources.

Internationally, the issue of irregular immigration is highly contested and actors promote different frames in the news. In this article, we analyze the strategizing that goes on behind the scenes among nongovernmental organizations and public immigration authorities. Many studies have documented how strategic actors take advantage of mainstream news media conventions, but there is a dearth of research on how these frame sponsors critically reflect on their strategies. Based on ethnographic fieldwork and qualitative interviews, we analyze the dilemmas and challenges the actors face in adapting their communication strategies to the news media. The immigration authorities are systematic and professional in their media work, with easy access to leading media. Faced with the news media's emphasis on dramatic individual stories, however, they struggle to find a media strategy that balances efficient communication with bureaucratic regulations and values. The NGOs, on the other hand, have the opportunity to exploit media conventions and pitch emotional, individual stories to journalists. Still, for both type of actors, the challenge is to expand the media interest beyond such stories to foster a systemic debate on immigration policy.

Social media (SoMe) platforms provide potentially important information for news journalists during everyday work and in crisis-related contexts. The aims of this study were (a) to map central journalistic challenges and emerging practices related to using SoMe for collecting and validating newsworthy content; and (b) to investigate how practices may contribute to a user-friendly design of a web-based SoMe content validation toolset. Interviews were carried out with 22 journalists from three European countries. Information about journalistic work tasks was also collected during a crisis training scenario (N = 5). Results showed that participants experienced challenges with filtering and estimating trustworthiness of SoMe content. These challenges were especially due to the vast overall amount of information, and the need to monitor several platforms simultaneously. To support improved situational awareness in journalistic work during crises, a user-friendly tool should provide content search results representing several media formats and gathered from a diversity of platforms, presented in easy-to-approach visualizations. The final decision-making about content and source trustworthiness should, however, remain as a manual journalistic task, as the sample would not trust an automated estimation based on tool algorithms.