Identification of innovation drivers based on technology-related news articles
Innovations contribute to economic growth. Hence, knowledge about drivers of innovation activities is a necessary input for economic policymaking when it comes to implement targeted support measures. We focus on firms as potential drivers of innovation and use a novel data-driven approach to identif...
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| Veröffentlicht in: | MAGKS - Joint Discussion Paper Series in Economics (Band 01-2024) |
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| Autoren: | , , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
Philipps-Universität Marburg
2024
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| Schlagworte: | |
| Online-Zugang: | PDF-Volltext |
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| Zusammenfassung: | Innovations contribute to economic growth. Hence, knowledge about drivers of innovation activities is a necessary input for economic policymaking when it comes to implement targeted support measures. We focus on firms as potential drivers of innovation and use a novel data-driven approach to identify them. The approach is based on news articles from a technology-related newspaper for the period 1996–2021. In a first step, natural language processing (NLP) tools are used to identify latent topics in the text corpus. Expert knowledge is used to tag innovation-related topics. In a second step, a named entity recognition (NER) method is used to detect firm names in the news articles. Combining the information about innovation-related topics and firms mentioned in news articles linked to these topics provides a set of firms linked to each innovation-related topic. The results suggest that the approach helps identifying drivers of innovation activities going beyond the usual suspects. However, given that the rate of false alarms is not negligible, at the end also human judgement is needed when using this approach. |
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| ISSN: | 1867-3678 |
| DOI: | 10.17192/es2024.0927 |