TY  - JOUR
PY  - 2023//
TI  - Examining shifts in public discourse on electric mobility adoption through Twitter data
JO  - Transportation research part D: transport and environment
A1  - Balla, Sai Naveen
A1  - Pani, Agnivesh
A1  - Sahu, Prasanta K.
A1  - González-Feliu, Jesús
SP  - e103843
EP  - e103843
VL  - 121
IS  - 
N2  - Most of the past research on public attitudes or choices on electric vehicles (EVs) have used user survey data (i.e., at a microscopic level). This paper adopts a multi-method approach to conduct a data-driven exploration of public sentiment evolution using a public tweet database spread across the last decade (2012-2022) (i.e., at a macroscopic level). Data mining from Twitter has enabled this research to obtain a rich alternative source of public sentiments on EVs. Natural Language Processing (NLP) techniques were then used to analyse the evolution in sentiments and reveal the underlying patterns in the discourse on EVs. <br><br>RESULTS and discussions in this paper categorise the shifts in public opinion and recognise critical linkages of economic summits or global events to sentiment changes. The research outcomes are expected to offer a strategic vantage point on the evolution of public discourse related to EV adoption and assist in designing better transportation electrification policies.<p />  <p>Language: en</p>
LA  - en
SN  - 1361-9209
UR  - http://dx.doi.org/10.1016/j.trd.2023.103843
ID  - ref1
ER  -