Modes and forms of communication have evolved drastically over the last several decades, with the emergence of large social media platforms and an increased accessibility to information over the Internet. Traditionally, journalists played the role of both providing and curating information to the general public, but with these new forms of communication, the role of journalists is evolving too. We examine how this role is changing in the crisis context. Specifically, we look at the interactions between journalists, citizens and government information workers after the Oso Landslide that occurred on March 22 of 2014. We analyzed the tweets from this event to see the interaction between these groups at specific points in time as the crisis unfolded. From a collection of ~1 million tweets, we conducted a micro-analysis of two important time periods: 1) all tweets about the Slide in the first two hours after it occurred and 2) all tweets over the first three weeks that included the hashtag created by the lead response agency (530slide.) We combine ethnographic analyses, descriptive statistics, and network analyses to better understand how contemporary crisis information is shared among these groups as presented on Twitter. Preliminary results show that there were common content themes that each represent a specific ‘information need’: situational awareness, public safety, aid, and commentary. 

At a time of heightened global attention to the threat of misinformation, disinformation, political propaganda, and the role of technology in facilitating their spread, this research addresses the media ecosystem encompassing the Syrian Civil War. We examine the competing narratives surrounding the role of Syria Civil Defence, a volunteer humanitarian organization popularly known as the White Helmets, working in war-torn Syria. Mainstream media articles sympathetic of the White Helmets and their efforts brought global awareness to the plight of Syrian people, especially those resisting the Assad government. However, this narrative was not aligned with other views of the complex geopolitical landscape of the Syrian conflict, and in response counter-narratives challenging the White Helmets emerged and spread to other online communities. Using a mixed-method approach based on seed data collected from Twitter, and then extending out to the websites cited in that data, we examine content sharing practices within news articles across distinct media domains that functioned to construct, shape, and propagate these narratives. We articulate a predominantly alternative media “echo-system” of websites that repeatedly share content about the White Helmets. Among other findings, our work reveals a small set of websites and authors generating content that is spread across diverse sites, drawing audiences from distinct communities into a shared narrative. This analysis also reveals the integration of government-funded media and geopolitical think tanks as source content for anti-White Helmets narratives. More broadly, the analysis demonstrates the role of alternative newswire-like services in providing content for alternative media websites. Though additional work is needed to understand these patterns over time and across topics, we provide insight into the dynamics of this multi-layered media ecosystem.

An important and under-explored component of information exchange and diffusion on social media involves permutations—i.e. how information changes, or more accurately, is changed as it flows. In this research paper, we aim to identify the various rumors and narratives that exist within a conversation surrounding Omran Daqneesh, the ‘Aleppo Boy’, on Twitter, and to investigate the actions that users take to propagate a certain permutations of these narratives. Before we can see how narratives propagate, we must first seek to understand these narratives at various levels of analysis, representing both the individual and society more generally. To this end, we examine narratives within the conversation at various levels: the micro, meso, and macro, representing individual actions and rumors, context-specific narratives, and a higher-level beliefs and worldviews. In this research we adopt a mixed methods approach. We quantitatively analyze our data to gain insights into the key events and influential actors in the space, and qualitatively code tweets to identify 1) rumor permutations that contribute to larger narratives surrounding the Syrian conflict; and 2) specific actions that help us to understand how individuals interacting within this information space. We aim to build a deeper understanding of how rumors are spread, how disinformation effects the online information space, and to develop a robust coding scheme that is transferable and can be applied to other rumors outside of the Syrian context in the future.