TY - JOUR
T1 - User Satisfaction in the New Energy Vehicles
T2 - 10th International Conference on Information Technology and Quantitative Management, ITQM 2023
AU - Xu, Zhaoguang
AU - Gui, Shumeng
AU - Dang, Yanzhong
AU - Li, Xianneng
N1 - Publisher Copyright:
© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the Tenth International Conference on Information Technology and Quantitative Management.
PY - 2023
Y1 - 2023
N2 - Automotive forums offer abundant and genuine data from car enthusiasts, enabling larger-scale customer satisfaction research. Current studies utilizing forum data for customer satisfaction measurement tend to be coarse-grained due to the intricacy of automotive products. As such, we introduce an improved aspect attention-based BiLSTM with aspect embedding (AATAE_BiLSTM) model, precisely identifying users' aspect-level sentiment tendencies. Employing a hierarchical indicator system, we capture users' sentiment tendencies at three levels, from fine-grained to coarse-grained. Moreover, we present a novel comprehensive quantitative model of satisfaction and attention based on sentiment tendencies, facilitating the measurement of users' satisfaction and attention across different indicator levels. We analyze BYD's NEV word-of-mouth comments data from AutoHome to gauge user satisfaction with BYD NEVs. Our study offers valuable insights for NEV companies to enhance their products and increase competitiveness.
AB - Automotive forums offer abundant and genuine data from car enthusiasts, enabling larger-scale customer satisfaction research. Current studies utilizing forum data for customer satisfaction measurement tend to be coarse-grained due to the intricacy of automotive products. As such, we introduce an improved aspect attention-based BiLSTM with aspect embedding (AATAE_BiLSTM) model, precisely identifying users' aspect-level sentiment tendencies. Employing a hierarchical indicator system, we capture users' sentiment tendencies at three levels, from fine-grained to coarse-grained. Moreover, we present a novel comprehensive quantitative model of satisfaction and attention based on sentiment tendencies, facilitating the measurement of users' satisfaction and attention across different indicator levels. We analyze BYD's NEV word-of-mouth comments data from AutoHome to gauge user satisfaction with BYD NEVs. Our study offers valuable insights for NEV companies to enhance their products and increase competitiveness.
KW - aspect-level sentiment analysis
KW - customer satisfaction
KW - new energy vehicle
KW - user-generated content
UR - http://www.scopus.com/inward/record.url?scp=85171757358&partnerID=8YFLogxK
U2 - 10.1016/j.procs.2023.08.112
DO - 10.1016/j.procs.2023.08.112
M3 - Conference article
AN - SCOPUS:85171757358
SN - 1877-0509
VL - 221
SP - 1242
EP - 1249
JO - Procedia Computer Science
JF - Procedia Computer Science
Y2 - 12 August 2023 through 14 August 2023
ER -