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arXiv · 2312.10650

Towards Designing a Question-Answering Chatbot for Online News: Understanding Questions and Perspectives

Md Naimul Hoque·Ayman Mahfuz·Mayukha Kindi·Naeemul Hassan
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Abstract

Large Language Models (LLMs) have created opportunities for designing chatbots that can support complex question-answering (QA) scenarios and improve news audience engagement. However, we still lack an understanding of what roles journalists and readers deem fit for such a chatbot in newsrooms. To address this gap, we first interviewed six journalists to understand how they answer questions from readers currently and how they want to use a QA chatbot for this purpose. To understand how readers want to interact with a QA chatbot, we then conducted an online experiment (N=124) where we asked each participant to read three news articles and ask questions to either the author(s) of the articles or a chatbot. By combining results from the studies, we present alignments and discrepancies between how journalists and readers want to use QA chatbots and propose a framework for designing effective QA chatbots in newsrooms.

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Md Naimul Hoque, Ayman Mahfuz, Mayukha Kindi, Naeemul Hassan. 2023-12-17. Towards Designing a Question-Answering Chatbot for Online News: Understanding Questions and Perspectives. https://arxiv.org/abs/2312.10650

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