ACA-ScoreTM v2: Desarrollo y refinamiento de un índice metodológico para la medición de Autoridad Algorítmica en Relaciones Públicas y Comunicación Estratégica

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Authors: Sonia Yánez Blum
Cited by: 0

Abstract

The acceleration of generative artificial intelligence in communication ecosystems has created a gap between public relations professional practice and available instruments to measure its algorithmic impact. This article documents the development and refinement process of ACA-Score™ v2 —a methodological index for measuring Algorithmic Authority and Credibility (ACA™)— following Churchill's (1979) paradigm for scale development. The instrument operates with 4 equally weighted pillars (Traceability, Coherence, Depth, Currency), 12 Likert 1-5 KPIs, and a canonical formula producing a 0-to-100 index. Construct relevance is supported by two exploratory surveys of Latin American communication professionals (August 2025, n=130; January-February 2026, n=5), consistent with the demand for algorithmic verification instruments. As an operational extension of the framework, the 6 PR 6.0 KPIs are presented —specific indicators for professional practice at the algorithmic level— including three original contributions: Algorithmic Credibility, Multichannel Narrative Consistency, and Spokesperson Impact in AI Cycle, with a four-type algorithmic citation taxonomy. Confirmatory validation (CFA, N≥200) is planned for Q4 2026.

Fields of Study & Subjects

Public Relations and Crisis Communication Digital Marketing and Social Media News Media Framing and Political Communication

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
15 March 2026
Language
ES
Document type
Preprint