Many actors use strategic communications to impact media debates through targeted messages and campaigns, but the scale and diversity of online media content make it difficult to evaluate the impact of a particular message or campaign. In this paper, we present a new technique that leverages semantic similarity of actor messages and media content to quantify the change in media discourse after a particular message has been published. We demonstrate our approach by measuring the impact of press releases from environmentally-active organisations on social media discussions about climate change. Our results show a heavy-tailed distribution of responses to these strategic communications, suggesting that relatively few messages have a substantive impact on online discourse.

Despite the importance of visual imagery for how people conceptualise issues in the news media, most research on journalism and communication prioritises textual media. This research examines the visual imagery accompanying news stories about the 2021 UN Climate Summit in Glasgow (COP26). First, we find that the visual discourse of COP26 is limited to politicians and “talking heads” imagery, and images of protest. Second, we explore the journey that images take through the news media ecosystem, from the camera lens to the published news article, identifying the sources of power which act on visuals throughout this journey. Overall, we empirically demonstrate the importance of understanding the networked nature of images and how they move through a complex globalised media ecosystem, rather than conceptualising them simply as static objects in the news cycle.

Online communications, and in particular social media, are a key component of how society interacts with and promotes content online. Collective attention on such content can vary wildly. The majority of breaking topics quickly fade into obscurity after only a handful of interactions, while the possibility exists for content to ``go viral'', seeing sustained interaction by large audiences over long periods. In this paper we investigate the mechanisms behind such events and introduce a new representation that enables direct comparison of events over diverse time and volume scales. We find four characteristic behaviours in the usage of hashtags on Twitter that are indicative of different patterns of attention to topics. We go on to develop an agent-based model for generating collective attention events to test the factors affecting emergence of these phenomena.