Text mining as a tool for real-time technology assessment: Application to the cross-national comparative study on artificial organ technology

Abstract

This study proposed a methodology that integrate sociotechnical systems (STS) and media big data analysis using text mining for the new, real-time technology assessment (TA). The essential steps of this method are composed of data collection using a cultural map, analysis with trends and patents, and synthesis using media big data. By applying this methodology to artificial organs, first, we have shown that STS can be apply to biosocial technical systems beyond the sustainability transition. The result reveals that a media discourse structures, in which eight countries began to form socio-technical regimes around technologies with their respective strengths, in an objective way. Each technology corresponded to the vested interests in each country's socio-technical regimes. These discourse structures helped us to identify substitution, two types of transformation, and reconfiguration as transition pathways. More importantly, our analysis results have also shown that the methodology helps to overcome the anticipation dilemma, saving the time and resources required for TA. Our integrated methodology has achieved similar results by using 23% of the budget, 25% of the time, and 14% of the work hours used for official TA. Lastly, the "objectivity" and "agenda setting" of this methodology can provide a breakthrough in overcoming the control dilemma.