Detecting Emerging Technologies in Artificial Intelligence Scientific Ecosystem Using an Indicator-based Model

October 06, 2022 Β· Declared Dead Β· πŸ› arXiv.org

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Ali Ghaemmaghami, Andrea Schiffauerova, Ashkan Ebadi arXiv ID 2211.01348 Category cs.DL: Digital Libraries Cross-listed cs.AI, cs.CL, cs.SI Citations 0 Venue arXiv.org Last Checked 3 months ago
Abstract
Early identification of emergent topics is of eminent importance due to their potential impacts on society. There are many methods for detecting emerging terms and topics, all with advantages and drawbacks. However, there is no consensus about the attributes and indicators of emergence. In this study, we evaluate emerging topic detection in the field of artificial intelligence using a new method to evaluate emergence. We also introduce two new attributes of collaboration and technological impact which can help us use both paper and patent information simultaneously. Our results confirm that the proposed new method can successfully identify the emerging topics in the period of the study. Moreover, this new method can provide us with the score of each attribute and a final emergence score, which enable us to rank the emerging topics with their emergence scores and each attribute score.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Digital Libraries

Died the same way β€” πŸ‘» Ghosted