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@article{210779,
        author = {Pendem Satya Pawan and Dr. Bonthu Kotaiah},
        title = {Empirical Evaluation of Synthetic Opinion Cascades and Algorithmic Phase Transitions in Multi-Agent Social Networks},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {6},
        pages = {2145-2151},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=210779},
        abstract = {Automated evaluation systems for content moderation and credibility assessments are increasingly used to govern public discourse and citizen grievances, but their susceptibility to social linguistic biases is difficult to evaluate in practice. This paper proposes a counterfactual audit framework for evaluating how different registers of language influence automated content moderation and credibility assessments. By comparing counterfactual statements that make identical social claims, utility-related grievances, and healthcare-related complaints, but use either formal-standard or vernacular-informal registers of language, we can assess the extent to which automated credibility assessments differ based on register choice. We find that credibility scores for equivalent statements tend to be lower for colloquial registers relative to formal-standard variants. We then apply our method to an interactive auditing tool that tracks credibility divergence (), civility divergence (), and automatic disparity flags in real-time to help ensure that vernacular civic discourse is not unfairly suppressed by automated governance tools.},
        keywords = {Automated Content Moderation, Algorithmic Bias, Linguistic Register, Credibility Divergence, Counterfactual Auditing, Socio-Linguistic Parity.},
        month = {November},
        }