Abstract
Despite the increasing popularity of the Quadruple Helix model in innovation studies, the model has suffered from a lack of robust measurements. This article contributes by proposing new measurements and social media data as the new empirical source of evaluation. We argue that social media data contain ample evidence of interactions within and across the Quadruple Helix and propose measurements using topic modelling and network analysis, well-established methods in the literature. We focused on a specific funding program, Tandem Industry-Academia (TIA), launched by the Finnish Research Impact Foundation in 2020. Based on Twitter data, we found a growing tendency for diversified public discourse and knowledge clusters. However, TIA did not improve inter-cluster interactions, a necessary condition for co-evolution. Our empirical case study suggests using social media data as complementary sources of the Quadruple Helix in the digital era.
Original language | English |
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Journal | Technological Forecasting and Social Change |
Volume | 194 |
Number of pages | 14 |
ISSN | 0040-1625 |
DOIs | |
Publication status | Published - Sep 2023 |
MoE publication type | A1 Journal article-refereed |
Fields of Science
- 518 Media and communications
- Big data
- Evaluation
- Network analysis
- Quadruple Helix
- Social media
- Topic modelling
- University -industry