# User Experience Design for Automatic Credibility Assessment of News Content About COVID-19

arXiv: https://arxiv.org/abs/2204.13943 · HTML: https://mlsanity.com/paper/2204.13943/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 78 references that are in the map.
- First posted on arXiv 29 Apr 2022.

## Builds on (most cited first, 14 of 14)

- [BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models](https://mlsanity.com/paper/2104.08663/) (2021)
- [HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification](https://mlsanity.com/paper/2011.03088/) (2020)
- [Generating Fact Checking Explanations](https://mlsanity.com/paper/2004.05773/) (2020)
- [QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension](https://mlsanity.com/paper/2107.12708/) (2021)
- [Fighting an Infodemic: COVID-19 Fake News Dataset](https://mlsanity.com/paper/2011.03327/) (2020)
- [ReCOVery: A Multimodal Repository for COVID-19 News Credibility Research](https://mlsanity.com/paper/2006.05557/) (2020)
- [On the Detection of Disinformation Campaign Activity with Network Analysis](https://mlsanity.com/paper/2005.13466/) (2020)
- [Assessing the risks of "infodemics" in response to COVID-19 epidemics](https://mlsanity.com/paper/2004.03997/) (2020)
- [CODO: An Ontology for Collection and Analysis of Covid-19 Data](https://mlsanity.com/paper/2009.01210/) (2020)
- [A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection](https://mlsanity.com/paper/2101.03545/) (2021)
- [Exploring Lightweight Interventions at Posting Time to Reduce the Sharing of Misinformation on Social Media](https://mlsanity.com/paper/2101.11824/) (2021)
- [European Language Grid: An Overview](https://mlsanity.com/paper/2003.13551/) (2020)
- [Determining the Credibility of Science Communication](https://mlsanity.com/paper/2105.14473/) (2021)
- [Making Metadata Fit for Next Generation Language Technology Platforms: The Metadata Schema of the European Language Grid](https://mlsanity.com/paper/2003.13236/) (2020)

## Abstract (arXiv)

The increasingly rapid spread of information about COVID-19 on the web calls for automatic measures of quality assurance. In that context, we check the credibility of news content using selected linguistic features. We present two empirical studies to evaluate the usability of graphical interfaces that offer such credibility assessment. In a moderated qualitative interview with six participants, we identify rating scale, sub-criteria and algorithm authorship as important predictors of the usability. A subsequent quantitative online survey with 50 participants reveals a conflict between transparency and conciseness in the interface design, as well as a perceived hierarchy of metadata: the authorship of a news text is more important than the authorship of the credibility algorithm used to assess the content quality. Finally, we make suggestions for future research, such as proactively documenting credibility-related metadata for Natural Language Processing and Language Technology services and establishing an explicit hierarchical taxonomy of usability predictors for automatic credibility assessment.