Consumer insight on driverless automobile technology adoption via twitter data: A sentiment analytic approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F20%3A63526218" target="_blank" >RIV/70883521:28120/20:63526218 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/70883521:28140/20:63526218

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-030-64849-7_41" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-64849-7_41</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-64849-7_41" target="_blank" >10.1007/978-3-030-64849-7_41</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Consumer insight on driverless automobile technology adoption via twitter data: A sentiment analytic approach

Popis výsledku v původním jazyce

Technology has sped up the innovation effort in the automobile industry. Further to this automobile innovation such as intelligent climate control, adaptive cruise control, and others, we find in today’s vehicles, it has been predicted that by 2030, there will be driverless vehicles, of which samples are already on the market. The news and the sights of these so-called driverless vehicles have generated mixed reactions, and this motivated our study. Hence the present study focuses on a dataset of tweets associated with driverless vehicles downloaded using the Twitter API. Valence Aware Dictionary and sentiment Reasoner (VADER), a lexicon and rule-based sentiment analysis tool were used in extracting sentiments on the tweets to gauge public opinions about the acceptance and adoption of the driverless vehicles ahead of their launch. The VADER sentiment analysis results, however, show that the general discussion on driverless vehicles was positive. Besides, we generated a word cloud to visually analyze the terms in the dataset to gain further insights and understand the messages conveyed by the tweets in other to enhance the usage and adoption of driverless vehicles. This study will enable self-driving vehicle technology service providers and autonomous vehicle manufacturers to gain more insights on how to transform the transportation sector by investing in research and technology. © 2020, IFIP International Federation for Information Processing.

Název v anglickém jazyce

Consumer insight on driverless automobile technology adoption via twitter data: A sentiment analytic approach

Popis výsledku anglicky

Technology has sped up the innovation effort in the automobile industry. Further to this automobile innovation such as intelligent climate control, adaptive cruise control, and others, we find in today’s vehicles, it has been predicted that by 2030, there will be driverless vehicles, of which samples are already on the market. The news and the sights of these so-called driverless vehicles have generated mixed reactions, and this motivated our study. Hence the present study focuses on a dataset of tweets associated with driverless vehicles downloaded using the Twitter API. Valence Aware Dictionary and sentiment Reasoner (VADER), a lexicon and rule-based sentiment analysis tool were used in extracting sentiments on the tweets to gauge public opinions about the acceptance and adoption of the driverless vehicles ahead of their launch. The VADER sentiment analysis results, however, show that the general discussion on driverless vehicles was positive. Besides, we generated a word cloud to visually analyze the terms in the dataset to gain further insights and understand the messages conveyed by the tweets in other to enhance the usage and adoption of driverless vehicles. This study will enable self-driving vehicle technology service providers and autonomous vehicle manufacturers to gain more insights on how to transform the transportation sector by investing in research and technology. © 2020, IFIP International Federation for Information Processing.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50204 - Business and management

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation

ISBN

978-3-030-64860-2

ISSN

—

e-ISSN

—

Počet stran výsledku

11

Strana od-do

463-473

Název nakladatele

Springer

Místo vydání

Cham

Místo konání akce

Tiruchirappalli

Datum konání akce

17. 12. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—