2022/10/06 by Ali Ghaemmaghami, Ghaemmaghami, Ali, Andrea Schiffauerova +3
Business, Management and Accounting · Decision Sciences · #Artificial Intelligence (cs.AI) #Big Data and Business Intelligence #Computation and Language (cs.CL) #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Innovation Diffusion and Forecasting #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2211.01348
openalex publication_date 2022/10/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.