Exploring the boundaries of open innovation: Evidence from social media mining

José Ramón Saura, Daniel Palacios‐Marqués, Domingo Ribeiro Soriano · 2022 · Technovation

Summary. This study analyzes Twitter conversations about open innovation using machine learning and topic modeling to identify public sentiment and key themes. The analysis of nearly 600,000 tweets reveals eight major topics, with negative sentiment concentrated in culture and business model discussions, positive sentiment in community and creative projects, and neutral sentiment in entrepreneurship and technology. The researchers identify 20 limitations of open innovation based on this social media evidence.

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Saura, J. R., Palacios‐Marqués, D., & Soriano, D. R.. (2022). Exploring the boundaries of open innovation: Evidence from social media mining. Technovation. https://doi.org/10.1016/j.technovation.2021.102447

@article{saura-2022-exploring-boundaries-open-innovation-evidence,
  title   = {Exploring the boundaries of open innovation: Evidence from social media mining},
  author  = {José Ramón Saura and Daniel Palacios‐Marqués and Domingo Ribeiro Soriano},
  journal = {Technovation},
  year    = {2022},
  doi     = {10.1016/j.technovation.2021.102447},
  url     = {https://doi.org/10.1016/j.technovation.2021.102447}
}

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TI  - Exploring the boundaries of open innovation: Evidence from social media mining
AU  - José Ramón Saura
AU  - Daniel Palacios‐Marqués
AU  - Domingo Ribeiro Soriano
JO  - Technovation
PY  - 2022
DO  - 10.1016/j.technovation.2021.102447
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Details

DOI: 10.1016/j.technovation.2021.102447
Countries: Spain
Regions: Europe
Categories: innovation-theory, innovation-networks, general-innovation
Added: 2026-04-28