# A new mapping of technological interdependence

arXiv: https://arxiv.org/abs/2308.00014 · HTML: https://mlsanity.com/paper/2308.00014/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 124 references that are in the map.
- First posted on arXiv 31 Jul 2023.

## Builds on (most cited first, 6 of 6)

- [Distinctiveness Centrality in Social Networks](https://mlsanity.com/paper/1912.03391/) (2019)
- [Brand Intelligence Analytics](https://mlsanity.com/paper/2001.11479/) (2020)
- [The dynamics of correlated novelties](https://mlsanity.com/paper/1310.1953/) (2013)
- [Classifying Patents Based on their Semantic Content](https://mlsanity.com/paper/1612.08504/) (2016)
- [Dynamic patterns of knowledge flows across technological domains: empirical results and link prediction](https://mlsanity.com/paper/1706.07140/) (2017)
- [As long as you talk about me: The importance of family firm brands and the contingent role of family-firm identity](https://mlsanity.com/paper/2110.13815/) (2021)

## Built on by (most cited first, 1 of 1)

- [A Global Dataset Mapping the AI Innovation from Academic Research to Industrial Patents](https://mlsanity.com/paper/2503.09257/) (2025)

## Abstract (arXiv)

How does technological interdependence affect innovation? We address this question by examining the influence of neighbors' innovativeness and the structure of the innovators' network on a sector's capacity to develop new technologies. We study these two dimensions of technological interdependence by applying novel methods of text mining and network analysis to the documents of 6.5 million patents granted by the United States Patent and Trademark Office (USPTO) between 1976 and 2021. We find that, in the long run, the influence of network linkages is as important as that of neighbor innovativeness. In the short run, however, positive shocks to neighbor innovativeness yield relatively rapid effects, while the impact of shocks strengthening network linkages manifests with delay, even though lasts longer. Our analysis also highlights that patent text contains a wealth of information often not captured by traditional innovation metrics, such as patent citations.