2024/09/16 by Yasser Saeid, Felix Neubürger, Saeid, Yasser +9
Social Sciences · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Terrorism, Counterterrorism, and Political Violence
paper · pdf · doi:10.48550/arxiv.2409.18984
openalex publication_date 2024/09/16 · openalex created_date 2024/10/28 · openalex updated_date 2026/07/28
This work investigates the identification of Charismatic Leadership Tactics (CLTs) in natural language using a fine-tuned Bidirectional Encoder Representations from Transformers (BERT) model. Based on an own extensive corpus of CLTs generated and curated for this task, our methodology entails training a machine learning model that is capable of accurately identifying the presence of these tactics in natural language. A performance evaluation is conducted to assess the effectiveness of our model in detecting CLTs. We find that the total accuracy over the detection of all CLTs is 98.96% The results of this study have significant implications for research in psychology and management, offering potential methods to simplify the currently elaborate assessment of charisma in texts.