Expressive Interviewing: A Conversational System for Coping with COVID-19

July 07, 2020 Β· Declared Dead Β· πŸ› NLP4COVID@EMNLP

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Authors Charles Welch, Allison Lahnala, VerΓ³nica PΓ©rez-Rosas, Siqi Shen, Sarah Seraj, Larry An, Kenneth Resnicow, James Pennebaker, Rada Mihalcea arXiv ID 2007.03819 Category cs.HC: Human-Computer Interaction Cross-listed cs.CL, cs.CY Citations 30 Venue NLP4COVID@EMNLP Last Checked 4 months ago
Abstract
The ongoing COVID-19 pandemic has raised concerns for many regarding personal and public health implications, financial security and economic stability. Alongside many other unprecedented challenges, there are increasing concerns over social isolation and mental health. We introduce \textit{Expressive Interviewing}--an interview-style conversational system that draws on ideas from motivational interviewing and expressive writing. Expressive Interviewing seeks to encourage users to express their thoughts and feelings through writing by asking them questions about how COVID-19 has impacted their lives. We present relevant aspects of the system's design and implementation as well as quantitative and qualitative analyses of user interactions with the system. In addition, we conduct a comparative evaluation with a general purpose dialogue system for mental health that shows our system potential in helping users to cope with COVID-19 issues.
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