AI RESEARCH
A New Semisupervised Technique for Polarity Analysis using Masked Language Models
arXiv CS.CL
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ArXi:2604.26230v1 Announce Type: new I developed a new version of Latent Semantic Scaling (LSS) employing word2vec as a masked language model. Unlike original spatial models, it assigns polarity scores to words and documents as predicted probabilities of seed words to occur in given contexts. These probabilistic polarity scores are accurate, interpretable and consistent than those spatial polarity models can produce in text analysis.