著者・編者Mejia, Caballero Cristian Andres
Mejia Caballero, Cristian Andres
一般注記This thesis explores the underlying dynamics between social attention, funding, and emerging technologies in order to discover patterns that may improve funding allocation strategies when it comes to select emerging research trends.
It is argued that social expectations of technologies represented by levels of attention extracted from printed media may play a role in the configuration of emergent research topics. To discover if such relation exist data from academic publishing and news articles are used, and analyzed by applying methods grounded in network theory, artificial intelligence, and text mining. Objectives and research background are discussed in the introductory Chapter 1.
The target of analysis is robotics research. Robotics is known for its social engagement and broad discussions in the media, and also for the greater interest of governments in funding robotics related technologies. Making it an exemplary case study. In chapter 2 it is identified the taxonomy of robotics, and research trends. This is done through a comprehensive bibliometric study of academic literature.
Even though bibliometrics help us to reveal the landscape of robotics, little can be inferred on how specific research clusters are connected to society as a whole. Chapter 3 takes steps in that direction. It is explored the interconnection of publishing patterns of academic articles in the previously identified clusters to actual levels of social expectations. News data is incorporated as representation of social opinion, from where levels of attention and sentiment polarity are observed. Peaks of inflated expectations in relation to robotics were revealed. Moreover, it was found how positive discussions in the media are reflected as an increase of publications for specific robotics topics in a posterior time.
In the interface of solving social issues and promoting academic research, lies funding. Public and private organizations reconfigure their funding allocation strategies in response to what they believe are the most pertinent topics to target. Chapter 4, develops a method to assess whether funding organizations target innovative research.
Finally, Chapter 5 brings together emergence, expectations, and funding. Parting from observations collected in the previous chapters it is attempted to stablish a theory of funding of emergent technologies based on social attention. It is expected that the findings discussed in this research serve to identify technologies that timely bring solution to the social concerns at hand, and provide a reference for better funding allocation strategies.
identifier:oai:t2r2.star.titech.ac.jp:50415155
一次資料へのリンクURLhttp://t2r2.star.titech.ac.jp/rrws/file/CTT100767843/ATD100000413/Mejia-2018-Thesis.pdf (fulltext)
連携機関・データベース国立情報学研究所 : 学術機関リポジトリデータベース(IRDB)(機関リポジトリ)