# Analyzing Self-Driving Cars on Twitter

arXiv: https://arxiv.org/abs/1804.04058 · HTML: https://mlsanity.com/paper/1804.04058/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Apr 2018.

## Built on by (most cited first, 1 of 1)

- [Mapping Technological Futures: Anticipatory Discourse Through Text Mining](https://mlsanity.com/paper/2504.02853/) (2025)

## Abstract (arXiv)

This paper studies users' perception regarding a controversial product, namely self-driving (autonomous) cars. To find people's opinion regarding this new technology, we used an annotated Twitter dataset, and extracted the topics in positive and negative tweets using an unsupervised, probabilistic model known as topic modeling. We later used the topics, as well as linguist and Twitter specific features to classify the sentiment of the tweets. Regarding the opinions, the result of our analysis shows that people are optimistic and excited about the future technology, but at the same time they find it dangerous and not reliable. For the classification task, we found Twitter specific features, such as hashtags as well as linguistic features such as emphatic words among top attributes in classifying the sentiment of the tweets.