社交媒体上的框架与情感:工作与智能机器的未来

Ayse Ocal, Kevin Crowston
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摘要

目的有关人工智能(AI)及其对工作场所的潜在影响的研究日益增多。以前的研究已经探讨了传统媒体如何报道人工智能和工作的未来,但目前的研究在探讨社交媒体如何报道人工智能方面还不够深入。本文旨在通过研究人们在社交媒体上发布信息时是如何构思工作和智能机器的未来的,从而填补这一空白。设计/方法/途径我们参考社交媒体对话中表达的构思,调查公众的解释、假设和期望。我们还对文本数据中表达的情感和态度进行了编码。我们使用计算机辅助文本分析,包括一个 BERTopic 模型和两个 BERT 文本分类模型(一个用于情感分析,另一个用于情绪分析),并辅以人工判断,分析了由 998 个独特的 Reddit 帖子标题及其相应的 16,611 条评论组成的语料库。我们在 "工作新世界 "这一总体框架下详细分析了三个子框架:(1) 智能机器对社会的总体影响;(2) 任务的承担(增强和替代);(3) 工作岗位的丧失。在对话中观察到的普遍态度略显积极,最常见的情绪类别是好奇。研究结果还有助于确定未来工作的研究方向。此外,企业、组织或行业可以采用框架方法来分析客户或工人的反应,甚至影响他们的反应。这项工作的另一个贡献是应用框架理论来解释人们是如何构思未来智能机器工作的。
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Framing and feelings on social media: the futures of work and intelligent machines
PurposeResearch on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.Design/methodology/approachWe investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed 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.FindingsDifferent interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.Originality/valueFindings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.
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