Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Public Perception of Generative AI on Twitter: An Empirical Study Based on Occupation and Usage
4
Zitationen
5
Autoren
2023
Jahr
Abstract
The emergence of generative AI has sparked substantial discussions, with the potential to have profound impacts on society in all aspects. As emerging technologies continue to advance, it is imperative to facilitate their proper integration into society, managing expectations and fear. This paper investigates users' perceptions of generative AI using 3M posts on Twitter from January 2019 to March 2023, especially focusing on their occupation and usage. We find that people across various occupations, not just IT-related ones, show a strong interest in generative AI. The sentiment toward generative AI is generally positive, and remarkably, their sentiments are positively correlated with their exposure to AI. Among occupations, illustrators show exceptionally negative sentiment mainly due to concerns about the unethical usage of artworks in constructing AI. People use ChatGPT in diverse ways, and notably the casual usage in which they "play with" ChatGPT tends to associate with positive sentiments. After the release of ChatGPT, people's interest in AI in general has increased dramatically; however, the topic with the most significant increase and positive sentiment is related to crypto, indicating the hype-worthy characteristics of generative AI. These findings would offer valuable lessons for policymaking on the emergence of new technology and also empirical insights for the considerations of future human-AI symbiosis.
Ähnliche Arbeiten
The spread of true and false news online
2018 · 7.959 Zit.
What is Twitter, a social network or a news media?
2010 · 6.629 Zit.
Social Media and Fake News in the 2016 Election
2017 · 6.382 Zit.
Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children's understanding of deception
1983 · 6.247 Zit.
The Matthew Effect in Science
1968 · 6.114 Zit.