2022/06/23 by Simone Balloccu, Ehud Reiter, Balloccu, Simone +1 · 1 citation
Computer Science · Social Sciences · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Innovative Human-Technology Interaction #Misinformation and Its Impacts #Recommender Systems and Techniques
paper · pdf · doi:10.48550/arxiv.2206.13435
openalex publication_date 2022/06/23 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Visual representation of data like charts and tables can be challenging to understand for readers. Previous work showed that combining visualisations with text can improve the communication of insights in static contexts, but little is known about interactive ones. In this work we present an NLG chatbot that processes natural language queries and provides insights through a combination of charts and text. We apply it to nutrition, a domain communication quality is critical. Through crowd-sourced evaluation we compare the informativeness of our chatbot against traditional, static diet-apps. We find that the conversational context significantly improved users' understanding of dietary data in various tasks, and that users considered the chatbot as more useful and quick to use than traditional apps.