The dataset consists of 22 transcripts with eleven interview participants. The data analysis took place through a two-track process. Each transcript was analysed individually by highlighting key passages and synthesising the main insights to ensure an integral understanding of each interview. All transcripts were also analysed collectively through manual coding with ATLAS.ti software to allow for an overview of recurring themes. Regular meetings were held by the principal researcher and the research assistants to discuss the codings and interpretation of each transcript.
\n\nThe research found that AI companions can become an important part of people’s lives by providing a sense of emotional support and understanding without judgement. Yet the lack of central aspects of otherness, like an inner world of experience, tends to lead to ambivalent attitudes towards the relationship. The analysis resulted in a coding scheme highlighting positive and negative characteristics of AI companions as experienced by users, effects on user well-being and self-understanding, tensions that mark the ways users make sense of the relationship, ambivalence in terms of the otherness of AI companions, and similarities and differences between the user and their AI companion.
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