Framing and feelings on social media: The futures of work and intelligent machines

Publication Type:

Journal Article


Information, Technology & People (2024)


Purpose: This study explores interpretations and feelings about futures of work and intelligent machines expressed on social media.

Design/methodology/approach: We investigate public interpretations, assumptions and expectations expressed in social media conversations through which users freely share their most recent ideas. In addition to frames, this study also coded the emotions and attitudes expressed in the text data. More specifically, a corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments were analyzed by using computer-aided textual analysis comprising a BERTopic model, and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment. Finally, relationships among frames and attitudes and frames and emotions were examined.

Findings: Twelve clusters were found that related to futures of work with intelligent machines. Based on the prior literature, two frames were chosen from these clusters and analyzed in detail: (1) general impacts of intelligent machines on wealth and society and (2) replacement of tasks (augmentation and substitution). The general attitude observed in conversations was positive, moreover the most common emotion category was approval. Findings also showed there are relationships between frames and attitudes and frames and emotions.

Originality: This work extends the prior literature on a topic relevant for academia and industry. Findings of this research can help realize potential needs and benefits from the public’s vantage point in the case of possible transformations in the future of work with intelligent machines. The findings may also help enlighten researchers to shape research directions about futures of work. Furthermore, firms, organizations or industries may also employ framing methods to receive customers’ or workers’ responses, or even to influence the responses. Aside from the empirical findings, another crucial implication of this work is application of theory of technological frames for systematizing the interpretations of how people conceptualize the future of work with the technology of intelligent machines. This study constitutes a bridge that connects fields of IS, computational science and empirical social research.

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