TY - GEN
T1 - Detecting Themes Related to Public Concerns and Consumer Issues Regarding Personal Mobility
AU - Li, Xu
AU - Yeo, Harim
AU - Hwang, Hyesun
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - This study is conducted to explore the problems that are being discussed in society and investigate consumers’ feelings or experiences regarding personal mobility which have been started to receive attention, by conducting both news and social data analysis. Using the R 3.5.3 and Trendup 4.0 programs, this study gathered 1163 news reports and 10332 twitter reviews regarding personal mobility dating to the period between January 1, 2019 and December 31, 2019. Topics were extracted from the selected news reports through Latent Dirichlet Allocation (LDA) topic-modeling; the news and twitter reviews were analyzed using the bigram network analysis. The results of topic modeling show that issues related to personal mobility in news data included safety issues related to operation and for the product itself, growth issues for companies, and service issues such as sharing services. The results of the network analysis showed that the news data contained content on sharing services, service releases, and safety issues. Twitter data showed both consumers’ desire to use personal mobility in their lives and concerns about the safety of it. It is recommended to continually identify and improve the problems consumers feel and reflect them in relevant regulations.
AB - This study is conducted to explore the problems that are being discussed in society and investigate consumers’ feelings or experiences regarding personal mobility which have been started to receive attention, by conducting both news and social data analysis. Using the R 3.5.3 and Trendup 4.0 programs, this study gathered 1163 news reports and 10332 twitter reviews regarding personal mobility dating to the period between January 1, 2019 and December 31, 2019. Topics were extracted from the selected news reports through Latent Dirichlet Allocation (LDA) topic-modeling; the news and twitter reviews were analyzed using the bigram network analysis. The results of topic modeling show that issues related to personal mobility in news data included safety issues related to operation and for the product itself, growth issues for companies, and service issues such as sharing services. The results of the network analysis showed that the news data contained content on sharing services, service releases, and safety issues. Twitter data showed both consumers’ desire to use personal mobility in their lives and concerns about the safety of it. It is recommended to continually identify and improve the problems consumers feel and reflect them in relevant regulations.
KW - Consumer issue
KW - Personal mobility
KW - Twitter
UR - https://www.scopus.com/pages/publications/85088750832
U2 - 10.1007/978-3-030-50726-8_21
DO - 10.1007/978-3-030-50726-8_21
M3 - Conference contribution
AN - SCOPUS:85088750832
SN - 9783030507251
T3 - Communications in Computer and Information Science
SP - 161
EP - 166
BT - HCI International 2020 - Posters - 22nd International Conference, HCII 2020, Proceedings
A2 - Stephanidis, Constantine
A2 - Antona, Margherita
PB - Springer
T2 - 22nd International Conference on Human-Computer Interaction, HCII 2020
Y2 - 19 July 2020 through 24 July 2020
ER -