Exploring Public Sentiments of Psychedelics Versus Other Substances: A Reddit-Based Natural Language Processing Study.

IF 2.1 4区 医学 Q2 PSYCHOLOGY, CLINICAL
Brandon Biba, Brian A O'Shea
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引用次数: 0

Abstract

New methods that capture the public's perception of controversial topics may be valuable. This study investigates public sentiments toward psychedelics and other substances through analyzes of Reddit discussions, using Google's cloud-based Natural Language Processing (NLP) infrastructure. Our findings indicate that illicit substances such as heroin and methamphetamine are associated with highly negative general sentiments, whereas psychedelics like Psilocybin, LSD, and Ayahuasca generally evoke neutral to slightly positive sentiments. This study underscores the effectiveness and cost efficiency of NLP and machine learning models in understanding the public's perception of sensitive topics. The findings indicate that online public sentiment toward psychedelics may be growing in acceptance of their therapeutic potential. However, limitations include potential selection bias from the Reddit sample and challenges in accurately interpreting nuanced language using NLP. Future research should aim to diversify data sources and enhance NLP models to capture the full spectrum of public sentiment toward psychedelics. Our findings support the importance of ongoing research and public education to inform policy decisions and therapeutic applications of psychedelics.

探索迷幻药与其他物质的公众情绪:一项基于reddit的自然语言处理研究。
捕捉公众对争议话题看法的新方法可能是有价值的。本研究使用b谷歌基于云的自然语言处理(NLP)基础设施,通过分析Reddit上的讨论,调查公众对迷幻药和其他物质的情绪。我们的研究结果表明,海洛因和甲基苯丙胺等非法物质与高度消极的总体情绪有关,而裸盖菇素、LSD和死藤水等致幻剂通常会引起中性或轻微的积极情绪。本研究强调了NLP和机器学习模型在理解公众对敏感话题的看法方面的有效性和成本效率。研究结果表明,网上公众对迷幻药的看法可能越来越多地接受它们的治疗潜力。然而,局限性包括来自Reddit样本的潜在选择偏差以及使用NLP准确解释微妙语言的挑战。未来的研究应该致力于多样化的数据来源,并加强NLP模型,以捕捉公众对迷幻药的全面情绪。我们的发现支持了正在进行的研究和公众教育的重要性,以告知政策决定和迷幻药的治疗应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.30
自引率
7.10%
发文量
62
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