Sentiment Bias

Sentiment bias, the systematic skew in emotional expression or interpretation within text data, is a significant concern across various NLP applications, particularly in opinion summarization and news reporting. Current research focuses on developing methods to detect and mitigate this bias, employing techniques like data augmentation with large language models, adversarial training, and the creation of bias indices to quantify and compare different models' performance. Addressing sentiment bias is crucial for ensuring fairness, objectivity, and ethical considerations in AI systems, impacting fields ranging from media analysis to automated decision-making.