  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.
