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    <abstract>This study explores how optimism and pessimism are expressed in social media by combining psycholinguistic profiling with model interpretability. Using the OPT dataset, we fine-tune a RoBERTa-based classifier and apply LIME to examine both the most confident and the most ambiguous predictions. We analyze the influential tokens driving these decisions and identify lexical patterns linked to affective intensity, certainty, and social orientation. A complementary LIWC-based analysis of ground truth labels reveals systematic differences in emotional tone and cognitive style. PCA projections further show that optimism and pessimism occupy overlapping yet distinguishable regions in psycholinguistic space. Our findings demonstrate the value of linguistic interpretability in understanding dispositional sentiment.</abstract>
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%0 Conference Proceedings
%T Optimism, Pessimism, and the Language between: Model Interpretability and Psycholinguistic Profiling
%A Tabusca, Stefana Arina
%A Dinu, Liviu P.
%Y Angelova, Galia
%Y Kunilovskaya, Maria
%Y Escribe, Marie
%Y Mitkov, Ruslan
%S Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era
%D 2025
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F tabusca-dinu-2025-optimism
%X This study explores how optimism and pessimism are expressed in social media by combining psycholinguistic profiling with model interpretability. Using the OPT dataset, we fine-tune a RoBERTa-based classifier and apply LIME to examine both the most confident and the most ambiguous predictions. We analyze the influential tokens driving these decisions and identify lexical patterns linked to affective intensity, certainty, and social orientation. A complementary LIWC-based analysis of ground truth labels reveals systematic differences in emotional tone and cognitive style. PCA projections further show that optimism and pessimism occupy overlapping yet distinguishable regions in psycholinguistic space. Our findings demonstrate the value of linguistic interpretability in understanding dispositional sentiment.
%U https://aclanthology.org/2025.ranlp-1.141/
%P 1224-1231

Markdown (Informal)

[Optimism, Pessimism, and the Language between: Model Interpretability and Psycholinguistic Profiling](https://aclanthology.org/2025.ranlp-1.141/) (Tabusca & Dinu, RANLP 2025)

• Optimism, Pessimism, and the Language between: Model Interpretability and Psycholinguistic Profiling (Tabusca & Dinu, RANLP 2025)

ACL

• Stefana Arina Tabusca and Liviu P. Dinu. 2025. Optimism, Pessimism, and the Language between: Model Interpretability and Psycholinguistic Profiling. In Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era, pages 1224–1231, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.