Exploring Robot Personality through Big Data Mining: A Century-Long Analysis from Google Books

INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION(2023)

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摘要
Human-robot interactions (HRIs) are significantly influenced by the personality of robots. However, research on robot personality from the perspective of big data text mining remains scarce. To address this gap, our study delves into the portrayal of Big Five personality traits in robots across millions of Google Books, spanning from 1920 to 2019. In this study, we identify intriguing trends in how robot personalities have been described over the years. Notably, we observe that the trait of openness has consistently been the most frequently cited Big Five personality factor throughout the twentieth century. Following closely are conscientiousness, agreeableness, extraversion, and neuroticism. However, a noteworthy shift occurs in the late twentieth century, where extraversion garners increasing attention, ultimately becoming the most prominent Big Five personality factor after 2010. Furthermore, our analysis uncovers a fascinating positivity bias in the portrayal of robot personality. Robots are more commonly depicted as extroverted rather than introverted and open rather than reserved. These trends also correlate with the evolution of core personality words. For instance, the term intellectual robot gradually yields to intelligent robot over the course of the twentieth century. Additionally, in the twenty-first century, social robot emerges as the most prevailing topic. Understanding the interplay between human records and their perception of robot personalities provides valuable insights into both real descriptions and ideal expectations of robots. This research serves as a critical reference for further advancements in robot personality studies, shedding light on the dynamic nature of HRIs.
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关键词
Robot personality,Big Five,big data mining,robot history,Google Books
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