Deakin University
Browse

File(s) not publicly available

Using Information-Seeking Argument Mining to Improve Service

Version 2 2024-06-01, 20:04
Version 1 2022-09-30, 04:40
journal contribution
posted on 2024-06-01, 20:04 authored by Bernd SkieraBernd Skiera, S Yan, J Daxenberger, M Dombois, I Gurevych
If service providers can identify reasons users are in favor of or against a service, they have insightful information that can help them understand user behavior and what they need to do to change such behavior. This article argues that the novel text-mining technique referred to as information-seeking argument mining (IS-AM) can identify these reasons. The empirical study applies IS-AM to news articles and reviews about electric scooter-sharing systems (i.e., a service enabling the short-term rentals of electric motorized scooters). Its results point to IS-AM as a promising technique to improve service; the data enable the authors to identify 40 reasons to use or not use electric scooter-sharing systems, as well as their importance to users. Furthermore, the results show that news articles are better data sources than reviews because they are longer and contain more arguments and, thus, reasons.

History

Journal

Journal of Service Research

Volume

25

Article number

109467052211108

Pagination

1-12

Location

London, England

ISSN

1094-6705

eISSN

1552-7379

Language

eng

Notes

In press

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

4

Publisher

SAGE Publications

Usage metrics

    Research Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC