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

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Hoque, Md Naimul, Mahfuz, Ayman, Kindi, Mayukha, Hassan, Naeemul
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866929286371344384
author Hoque, Md Naimul
Mahfuz, Ayman
Kindi, Mayukha
Hassan, Naeemul
author_facet Hoque, Md Naimul
Mahfuz, Ayman
Kindi, Mayukha
Hassan, Naeemul
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2312_10650
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Towards Designing a Question-Answering Chatbot for Online News: Understanding Questions and Perspectives
Hoque, Md Naimul
Mahfuz, Ayman
Kindi, Mayukha
Hassan, Naeemul
Human-Computer Interaction
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.
title Towards Designing a Question-Answering Chatbot for Online News: Understanding Questions and Perspectives
topic Human-Computer Interaction
url https://arxiv.org/abs/2312.10650