Public sentiments on the fourth industrial revolution: An unsolicited public opinion poll from Twitter
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866917108938440704 |
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| author | Abbonato, Diletta |
| author_facet | Abbonato, Diletta |
| contents | This paper establishes an empirical baseline of public sentiment toward Fourth Industrial Revolution (4IR) technologies across six European countries during the period 2006--2019, prior to the widespread adoption of generative AI systems. Employing transformer-based natural language processing models on a corpus of approximately 90,000 tweets and news articles, I document a European public sphere increasingly divided in its assessment of technological change: neutral sentiment declined markedly over the study period as citizens sorted into camps of enthusiasm and concern, a pattern that manifests distinctively across national contexts and technology domains. Approximately 6\% of users inhabit echo chambers characterized by sentiment-aligned networks, with privacy discourse exhibiting the highest susceptibility to such dynamics. These findings provide a methodologically rigorous reference point for evaluating how the introduction of ChatGPT and subsequent generative AI systems has transformed public discourse on automation, employment, and technological change. The results carry implications for policymakers seeking to align technological governance with societal values in an era of rapid AI advancement. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2411_14230 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Public sentiments on the fourth industrial revolution: An unsolicited public opinion poll from Twitter Abbonato, Diletta General Economics Economics Computers and Society Social and Information Networks This paper establishes an empirical baseline of public sentiment toward Fourth Industrial Revolution (4IR) technologies across six European countries during the period 2006--2019, prior to the widespread adoption of generative AI systems. Employing transformer-based natural language processing models on a corpus of approximately 90,000 tweets and news articles, I document a European public sphere increasingly divided in its assessment of technological change: neutral sentiment declined markedly over the study period as citizens sorted into camps of enthusiasm and concern, a pattern that manifests distinctively across national contexts and technology domains. Approximately 6\% of users inhabit echo chambers characterized by sentiment-aligned networks, with privacy discourse exhibiting the highest susceptibility to such dynamics. These findings provide a methodologically rigorous reference point for evaluating how the introduction of ChatGPT and subsequent generative AI systems has transformed public discourse on automation, employment, and technological change. The results carry implications for policymakers seeking to align technological governance with societal values in an era of rapid AI advancement. |
| title | Public sentiments on the fourth industrial revolution: An unsolicited public opinion poll from Twitter |
| topic | General Economics Economics Computers and Society Social and Information Networks |
| url | https://arxiv.org/abs/2411.14230 |