期刊名称：GI_FORUM - Journal for Geographic Information Science
电子版ISSN：2308-1708
出版年度：2018
卷号：1
页码：82-89
DOI：10.1553/giscience2018_01_s82
出版社：ÖAW Verlag, Wien
摘要：Innovation is one of the major drivers of economic growth, where spatial processes of knowledge spillover play a vital role. Current practices in assessing firms’ innovation activity, including patent analysis and questionnaires, suffer from severe limitations. In this paper, we propose a novel approach to estimate firms’ innovation activity based on the texts on their websites. We use an automated web-scraper to harvest text from the websites, then extract semantic topics in a self-learning, generative topic-modelling approach, and finally analyse these topics using an Artificial Neural Networks (ANN) method to assess each firm’s level of innovation. This procedure results in a large-scale dataset that will be used for further spatial economic analysis of the distribution of innovative firms and the processes that drive the development of innovation in firms.
关键词：firm location; microgeography; innovation; web scraping; Big Spatial Data; text mining; topic modelling; neural networks
