  The rapid development of social robots has challenged robotics and cognitive
sciences to understand humans' perception of the appearance of robots. In this
study, robot-associated words spontaneously generated by humans were analyzed
to semantically reveal the body image of 30 robots that have been developed
over the past decades. The analyses took advantage of word affect scales and
embedding vectors, and provided a series of evidence for links between human
perception and body image. It was found that the valence and dominance of the
body image reflected humans' attitude towards the general concept of robots;
that the user bases and usages of the robots were among the primary factors
influencing humans' impressions towards individual robots; and that there was a
relationship between the robots' affects and semantic distances to the word
``person''. According to the results, building body image for robots was an
effective paradigm to investigate which features were appreciated by people and
what influenced people's feelings towards robots.
