A Wide Evaluation of ChatGPT on Affective Computing Tasks

Mostafa M. Amin, Rui Mao, Erik Cambria, Bjorn W. Schuller

Research output: Contribution to journalArticlepeer-review

Abstract

With the rise of foundation models, a new artificial intelligence paradigm has emerged, by simply using general purpose foundation models with prompting to solve problems instead of training a separate machine learning model for each problem. Such models have been shown to have emergent properties of solving problems that they were not initially trained on. The studies for the effectiveness of such models are still quite limited. In this work, we widely study the capabilities of the ChatGPT models, namely GPT-4 and GPT-3.5, on 13 affective computing problems, namely aspect extraction, aspect polarity classification, opinion extraction, sentiment analysis, sentiment intensity ranking, emotions intensity ranking, suicide tendency detection, toxicity detection, well-being assessment, engagement measurement, personality assessment, sarcasm detection, and subjectivity detection. We introduce a framework to evaluate the ChatGPT models on regression-based problems, such as intensity ranking problems, by modelling them as pairwise ranking classification. We compare ChatGPT against more traditional NLP methods, such as end-to-end recurrent neural networks and transformers. The results demonstrate the emergent abilities of the ChatGPT models on a wide range of affective computing problems, where GPT-3.5 and especially GPT-4 have shown strong performance on many problems, particularly the ones related to sentiment, emotions, or toxicity. The ChatGPT models fell short for problems with implicit signals, such as engagement measurement and subjectivity detection.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalIEEE Transactions on Affective Computing
DOIs
StateAccepted/In press - 2024

Keywords

  • Affective computing
  • Affective Computing
  • Analytical models
  • Aspect-Based Sentiment Analysis
  • Chatbots
  • ChatGPT
  • Computational modeling
  • Emotions Intensity Ranking
  • Engagement Measurement
  • Foundation Models
  • GPT-4
  • Personality Assessment
  • Sarcasm Detection
  • Sentiment analysis
  • Sentiment Analysis
  • Sentiment Intensity Ranking
  • Subjectivity Detection
  • Suicide Tendency Detection
  • Task analysis
  • Toxicity Detection
  • Toxicology
  • Well-being Assessment

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