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

Source: [Towards Designing a Question-Answering Chatbot for Online News: Understanding Questions and Perspectives](<https://www.sota2.com/research/paper/68fa72a31e209131cea57b96>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:57:05.175Z

Authors: Md Naimul Hoque, Ayman Mahfuz, Mayukha Kindi, Naeemul Hassan

Published: 2023-12-17T08:30:45.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2312.10650>)

[PDF](<https://arxiv.org/pdf/2312.10650.pdf>)