Generative Large Language Models, pre-trained on a huge amount of human authored text, are showing emergent capabilities in understanding and accomplishing a variety of NLP and text comprehension tasks. Recently, interest is growing in understanding to what extent LLMs can support humans, or even replace them, in accomplishing non trivial data analysis tasks. In this paper, we explore OpenAI's GPT capabilities in online customer review analysis, a multi-step analysis activity which typically involves both human knowledge and predictive data analysis techniques (e.g. topic extraction, aspect-based sentiment analysis). We explore different interaction modalities where the LLM covers all or part of the analysis process, and provide a preliminary evaluation against human annotation outcomes.
Poster: LLMs for online customer reviews analysis: Oracles or tools? Experiments with GPT 3.5
Morbidoni C.
2023-01-01
Abstract
Generative Large Language Models, pre-trained on a huge amount of human authored text, are showing emergent capabilities in understanding and accomplishing a variety of NLP and text comprehension tasks. Recently, interest is growing in understanding to what extent LLMs can support humans, or even replace them, in accomplishing non trivial data analysis tasks. In this paper, we explore OpenAI's GPT capabilities in online customer review analysis, a multi-step analysis activity which typically involves both human knowledge and predictive data analysis techniques (e.g. topic extraction, aspect-based sentiment analysis). We explore different interaction modalities where the LLM covers all or part of the analysis process, and provide a preliminary evaluation against human annotation outcomes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
