Beyond facts – a survey and conceptualisation of claims in online discourse analysis

Analyzing statements of facts and claims in online discourse is subject of a multitude of research areas. Methods from natural language processing and computational linguistics help investigate issues such as the spread of biased narratives and falsehoods on the Web. Related tasks include fact-checking, stance detection and argumentation mining. Knowledge-based approaches, in particular works in knowledge base construction and augmentation, are concerned with mining, verifying and representing factual knowledge. While all these fields are concerned with strongly related notions, such as claims, facts and evidence, terminology and conceptualisations used across and within communities vary heavily, making it hard to assess commonalities and relations of related works and how research in one field may contribute to address problems in another. We survey the state-of-the-art from a range of fields in this interdisciplinary area across a range of research tasks. We assess varying definitions and propose a conceptual model – Open Claims – for claims and related notions that takes into consideration their inherent complexity, distinguishing between their meaning, linguistic representation and context. We also introduce an implementation of this model by using established vocabularies and discuss applications across various tasks related to online discourse analysis.

Report on the first workshop on bias in automatic knowledge graph construction at AKBC 2020

We report on the First Workshop on Bias in Automatic Knowledge Graph Construction (KG-BIAS), which was co-located with the Automated Knowledge Base Construction (AKBC) 2020 conference. Identifying and possibly remediating any sort of bias in knowledge graphs, or in the methods used to construct or query them, has clear implications for downstream systems accessing and using the information in such graphs. However, this topic remains relatively unstudied, so our main aim for organizing this workshop was to bring together a group of people from a variety of backgrounds with an interest in the topic, in order to arrive at a shared definition and roadmap for the future. Through a program that included two keynotes, an invited paper, three peer-reviewed full papers, and a plenary discussion, we have made initial inroads towards a common understanding and shared research agenda for this timely and important topic.