Web Mining of Firm Websites: A Framework for Web Scraping and a Pilot Study for Germany

Abstract

Nowadays, almost all (relevant) firms have their own websites which they use to publish information about their products and services. Using the example of innovation in firms, we outline a framework for extracting information from firm websites using web scraping and data mining. For this purpose, we present an easy and free-to-use web scraping tool for large-scale data retrieval from firm websites. We apply this tool in a large-scale pilot study to provide information on the data source (i.e. the population of firm websites in Germany), which has as yet not been studied rigorously in terms of its qualitative and quantitative properties. We find, inter alia, that the use of websites and websites’ characteristics (number of subpages and hyperlinks, text volume, language used) differs according to firm size, age, location, and sector. Web-based studies also have to contend with distinct outliers and the fact that low broadband availability appears to prevent firms from operating a website. Finally, we propose two approaches based on neural network language models and social network analysis to derive firm-level information from the extracted web data.

Keywords: Web Mining, Web Scraping, R&D, R&I, STI, Innovation, Indicators, Text Mining

JEL Classification: O30, C81, C88