Abstract

User acceptance of new technologies is a key aspect to implement successful human-robot teams at work. The acceptance of new technologies, according to the Unified theory of Acceptance and Use Model, is determined by user's behavioral intention to use a technology and based on performance expectancy, effort expectancy, social influence and facilitating conditions. Furthermore, it is influenced by the experience a user has made with the new technology in the past. As not everyone can make their own experiences with robots in the workplace, many develop a first opinion by media consumption. To get an overview on media opinions on robots in working contexts, we extracted and coded the tone of headlines of three major English online newspapers. Subsequently, we compared the results of a human coding team with an open source approach for sentiment analysis. The comparison between human coders and the algorithm showed diverging results. Based on our analysis a team of human coders seems to be better in tone coding of short text passages like headlines. The overall results showed a negative overall tone in online newspaper headlines from 2016 to 2018. While 24% of the identified headlines had a positive tone, 43% contained a negative tone and 33% of the included headlines were coded as neutral. The negative tone in headlines on robots at work and their possible impact on workers expectations should be taken into account when introducing these new technologies in work contexts to ensure a human-centered implementation.

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