Future applications of generative large language models: A data-driven case study on ChatGPT

• DOI: 10.1016/j.technovation.2024.103002
• Publication Date: 2024-03-29T12:21:17Z
• Authors: Filippo Chiarello; Vito Giordano; Irene Spada; Simone Barandoni; Gualtiero Fantoni
• Keywords: Generative model

This study delves into the evolving role of generative Large Language Models (LLMs). We develop a data-driven approach to collect and analyse tasks that users are asking LLMs. Thanks focus on this paper contributes give quantitative granular understanding potential influence LLMs in different business areas. Utilizing dataset comprising over 3.8 million tweets, we identify cluster 31,747 unique tasks, with specific case ChatGPT. To reach goal, proposed method combines two Natural Processing (NLP) Techniques, Named Entity Recognition (NER) BERTopic. The combination makes it possible clusters them areas (BERTopic). Our findings reveal wide spectrum applications, from programming assistance creative content generation, highlighting LLM's versatility. analysis highlighted six emerging application for ChatGPT: human resources, programming, social media, office automation, search engines, education. also examines implications these innovation management, proposing research agenda explore intersection identified areas, four stages process: idea screening/idea selection, development, diffusion/sales/marketing.