A Survey on Event-based News Narrative Extraction

Narratives are fundamental to our understanding of the world, providing us with a natural structure for knowledge representation over time. Computational narrative extraction is a subfield of artificial intelligence that makes heavy use of information retrieval and natural language processing techniques. Despite the importance of computational narrative extraction, relatively little scholarly work exists on synthesizing previous research and strategizing future research in the area. In particular, this article focuses on extracting news narratives from an event-centric perspective. Extracting narratives from news data has multiple applications in understanding the evolving information landscape. This survey presents an extensive study of research in the area of event-based news narrative extraction. In particular, we screened over 900 articles that yielded 54 relevant articles. These articles are synthesized and organized by representation model, extraction criteria, and evaluation approaches. Based on the reviewed studies, we identify recent trends, open challenges, and potential research lines.Comment: 37 pages, 3 figures, to be published in the journal ACM CSU

Watching the Watchdogs: Using Transparency Cues to Help News Audiences Assess Information Quality

The myriad of information sources available online can make it hard for the average reader to know whether a piece of content is credible or not. This research aims to understand if the public’s assessment of the credibility of information could be more accurate with the help of transparency features that act as heuristic cues under the elaboration likelihood model and the heuristic-systematic model, and if the cues increase cognitive absorption. Two between-subjects studies were performed, one with a young demographic (N = 68) and another with a representative sample of the adult population (N = 325). The stimuli contained information boxes designed to indicate that the story was not written in a traditional journalistic style (message cues) and missing background information on the author (source cues). Results show significant effects of the cues on credibility assessment and cognitive absorption

Evaluation of soil intervention values in mine tailings in northern Chile

The aim of this work is to show a methodological proposal for the analysis of soil intervention values in mine tailings in order to determine the intervention requirements in the commune of Andacollo in northern Chile. The purpose of this analysis is to guide the intervention policies of both private and public organizations. The evaluation method is based on the Dutch legislation. The usability of the proposed methods depends on the available geochemical data from soil samples; in particular, we tackle the case when information regarding clay percentage in the soil is not available. We use the concepts of a threshold factor and an adjusted threshold factor to calculate a weighted intervention ranking. In order to illustrate the utility of this methodological proposal, a case study is carried out with the prescribed approach. In particular, this work presents an analysis of the elements of environmental significance related to the mining activity (Hg, Cd, Pb, As, Cu, Ni, Zn, Cr) in the commune of Andacollo, Coquimbo Region, Chile. The analyzed samples are used to determine where the intervention of tailing deposits is necessary and where a solution to these environmental liabilities is required as soon as possible. Out of the 81 samples evaluated, it was found that 18 require a potential intervention, and of these samples, seven of them are associated with abandoned tailings that, in some cases, are located close to the town center itself, one sample is associated with active tailings and the other 10 with inactive tailings

Code and raw data for the article "Exploring the relationships between emotions in fake news"

<p>Code and data associated with the article "Exploring the relationships between emotions in fake news" by Luis Rojas Rubio, Claudio Meneses Villegas, and Brian Keith Normabuena. We use the FakeNewsNet data sets (GossipCop and PolitiFact) and the CoronaFake data set for our experiments.</p&gt