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How AI Shapes Public Sentiment on Agency, Parametric Reductionism and Digital Expression [abstract]

Title: How AI Shapes Public Sentiment on Agency, Parametric Reductionism and Digital Expression [abstract]
Authors: Moutinho, Rodrigo Asfora; Rohden , Simoni F.; Pinto, Diego Costa
Contributors: Information Management Research Center (MagIC) - NOVA Information Management School; NOVA Information Management School (NOVA IMS)
Publication Year: 2025
Collection: Repositório da Universidade Nova de Lisboa (UNL)
Subject Terms: parametric reduction; agency transference; topic modelling; sentiment analysis
Description: Moutinho, R. A., Rohden , S. F., & Pinto, D. C. (2025). How AI Shapes Public Sentiment on Agency, Parametric Reductionism and Digital Expression [abstract]. 162-166. Abstract from AIRSI 2025, Zaragoza, Spain. ; Artificial Intelligence (AI) has traditionally enabled data-driven decisions in different industries. Recently, have begun to incorporate intuitive and emphatic function, shifting from a business tool into a mainstream consumer technology (Flavián & Casaló, 2021; Huang & Rust 2018). To guide this investigation, we pose the following research questions: (1) How are societal constraints imposed by AI represented in public discourse, drawing from Valenzuela et al.'s (2024) AI Constraints Framework? (2) How do sentiment and topic patterns reflect concerns around agency, reductionism, and digital expression? ; publishersversion ; published
Document Type: conference object
Language: English
Relation: PURE: 122045399; https://hdl.handle.net/10362/187423
Availability: https://hdl.handle.net/10362/187423
Rights: openAccess
Accession Number: edsbas.5543BAAC
Database: BASE