@inproceedings{b8e170f7208b4c5b9143fda71166652b,
title = "Using customers' online reviews to identify and classify human robot interaction failures in domestic robots",
abstract = "Little information is available regarding which types of failures robots experience in domestic settings. To further the community's knowledge, we manually classified 3062 customer reviews of robotic vacuum cleaners on Amazon.com. The resulting database was analyzed and used to create a Natural Language Processing (NLP) model capable of predicting whether a review contains a description of a failure or not. The current work describes the initial analysis and model development process as well as preliminary findings.",
keywords = "Human-robot interaction, Social network analysis, User satisfaction, User-centered",
author = "Shanee Honig and Alon Bartal and Tal Oron-Gilad",
note = "Funding Information: The first author is supported by The Helmsley Charitable Trust through the Agricultural, Biological, Cognitive Robotics Initiative and the Marcus Endowment Fund, and by Ben-Gurion University through the High-tech, Bio-tech and Chemo-tech Scholarship. Publisher Copyright: {\textcopyright} 2020 ACM.; 15th Annual ACM/IEEE International Conference on Human Robot Interaction, HRI 2020 ; Conference date: 23-03-2020 Through 26-03-2020",
year = "2020",
month = mar,
day = "23",
doi = "10.1145/3371382.3378323",
language = "English",
series = "ACM/IEEE International Conference on Human-Robot Interaction",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "251--253",
booktitle = "HRI 2020 - Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction",
address = "United States",
}