@inproceedings{discovery10200112,
           title = {Reasoning About Group Polarization: From Semantic Games to Sequent Systems},
           pages = {70--87},
       booktitle = {Proceedings of 25th Conference on Logic for Programming, Artificial Intelligence and Reasoning},
          volume = {100},
            note = {Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License (CC BY-NC-ND 4.0), (https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en).},
       publisher = {Easy Chair},
         journal = {EPiC Series in Computing},
            year = {2024},
          editor = {Nikolaj Bj{\o}rner and Marijn Heule and Andrei Voronkov},
         address = {Port Louis, Mauritius},
           month = {May},
          series = {EPiC Series in Computing},
             url = {https://doi.org/10.29007/wptz},
          author = {Freiman, Robert and Olarte, Carlos and Pimentel, Elaine and Ferm{\"u}ller, Christian},
        abstract = {Group polarization, the phenomenon where individuals become more extreme after in- teracting, has been gaining attention, especially with the rise of social media shaping peo- ple's opinions. Recent interest has emerged in formal reasoning about group polarization using logical systems. In this work we consider the modal logic PNL that captures the no- tion of agents agreeing or disagreeing on a given topic. Our contribution involves enhancing PNL with advanced formal reasoning techniques, instead of relying on axiomatic systems for analyzing group polarization. To achieve this, we introduce a semantic game tailored for (hybrid) extensions of PNL. This game fosters dynamic reasoning about concrete net- work models, aligning with our goal of strengthening PNL's effectiveness in studying group polarization. We show how this semantic game leads to a provability game by systemically exploring the truth in all models. This leads to the first cut-free sequent systems for some variants of PNL. Using polarization of formulas, the proposed calculi can be modularly adapted to consider different frame properties of the underlying model.},
            issn = {2398-7340}
}