Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning

Martin Müller,Marcel Salathé,Manuel Schneider,Effy Vayena

doi:10.2196/17830

Abstract

BackgroundThe discovery of the CRISPR-Cas9–based gene editing method has opened unprecedented new potential for biological and medical engineering, sparking a growing public debate on both the potential and dangers of CRISPR applications. Given the speed of technology development and the almost instantaneous global spread of news, it is important to follow evolving debates without much delay and in sufficient detail, as certain events may have a major long-term impact on public opinion and later influence policy decisions.ObjectiveSocial media networks such as Twitter have shown to be major drivers of news dissemination and public discourse. They provide a vast amount of semistructured data in almost real-time and give direct access to the content of the conversations. We can now mine and analyze such data quickly because of recent developments in machine learning and natural language processing.MethodsHere, we used Bidirectional Encoder Representations from Transformers (BERT), an attention-based transformer model, in combination with statistical methods to analyze the entirety of all tweets ever published on CRISPR since the publication of the first gene editing application in 2013.ResultsWe show that the mean sentiment of tweets was initially very positive, but began to decrease over time, and that this decline was driven by rare peaks of strong negative sentiments. Due to the high temporal resolution of the data, we were able to associate these peaks with specific events and to observe how trending topics changed over time.ConclusionsOverall, this type of analysis can provide valuable and complementary insights into ongoing public debates, extending the traditional empirical bioethics toolset.

Highlights

Genome editing has many potential applications, ranging from gene therapy [1] to crop enhancement [2] and production of biomolecules [3,4]
We show that the mean sentiment of tweets was initially very positive, but began to decrease over time, and that this decline was driven by rare peaks of strong negative sentiments
Due to the high temporal resolution of the data, we were able to associate these peaks with specific events and to observe how trending topics changed over time

Summary

Introduction

Genome editing has many potential applications, ranging from gene therapy [1] to crop enhancement [2] and production of biomolecules [3,4]. Targeted gene editing has only become possible within the last decade [9,10] using a CRISPR-Cas9–based method. The experiment, conducted by a group of Chinese scientists, raised ethical concerns among researchers and the general public about the potential far-reaching consequences of introducing germline modifications [14,15]. Such ethical concerns include unexpected side effects on the evolution of humans, as well as cultural and religious arguments. The discovery of the CRISPR-Cas9–based gene editing method has opened unprecedented new potential for biological and medical engineering, sparking a growing public debate on both the potential and dangers of CRISPR applications. Given the speed of technology development and the almost instantaneous global spread of news, it is important to follow evolving debates without much delay and in sufficient detail, as certain events may have a major long-term impact on public opinion and later influence policy decisions

Methods

Results

Discussion

Conclusion