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Consumer Insight on Driverless Automobile Technology Adoption via Twitter Data: A Sentiment Analytic Approach

机译:消费者洞察通过Twitter数据采用无驱动汽车技术:一种情绪分析方法

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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.
机译:技术在汽车工业中加快了创新努力。继该汽车创新如智能气候控制,自适应巡航控制等,我们发现在当今的车辆中,它已被预测到2030年,将有无驱动的车辆,其中样本已经在市场上。这些所谓的无人驾驶车辆的新闻和景点产生了混合反应,这激励了我们的研究。因此,本研究重点介绍与使用Twitter API下载的无人驾驶车辆相关联的推文数据集。价值意识的词典和情绪推理(VADER),lexicon和基于规则的情绪分析工具用于提取推文的情绪,以规范公众关于接受和采用无人驾驶车辆的宣传。然而,VADER情绪分析结果表明,关于无人驾驶车辆的一般讨论是积极的。此外,我们生成了一个单词云,可视地分析数据集中的术语,以获得进一步的见解,并了解推文所传达的消息,以增强无驱动车辆的使用和采用。本研究将使自驾驶车辆技术服务提供商和自主车辆制造商能够通过投资研究和技术来改善如何改变运输部门的洞察力。

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