Index modeling and factor analysis in media studies

The subject of this article is the methodological foundations for applying index modelling and factor analysis to the measurement of reputation in digital media communications. The article addresses the problem of constructing valid measurement models that reflect the multidimensional nature of reputation as a media-communicative construct. The focus of analysis lies on the principles of constructing and aggregating mediametric indices, as well as the mechanisms for aligning them with stakeholder perception models. A particular emphasis is placed on examining the compatibility of both quantitative media indicators and qualitative audience assessments within a unified measurement space. Special attention is devoted to the methodological capabilities of factor analysis as a tool for identifying latent reputational factors and verifying the internal consistency of measurement constructs in the context of growing volumes of media data and increasing complexity of the digital communication environment. The methodological basis of the research comprises systemic and structural-functional approaches, enabling the interpretation of reputation as a hierarchically organised aggregate of interrelated parameters. Methods of comparative and conceptual analysis are employed for the typologisation of index models. The key instrument is factor analysis, applied to identify latent variables and verify the structural validity of models. The scientific novelty of the research consists in developing the conceptual foundations for integrating mediametric indices and stakeholder perception models into a unified index architecture for measuring reputation. For the first time, the thesis is substantiated that the isolated application of mediametric and perceptual approaches generates methodological limitations: the incomparability of data of different natures and the fragmentation of interpretive conclusions, which prevents obtaining a holistic picture of an organisation's reputational state. The methodological status of factor analysis in reputational research has been refined: it is considered not only as a tool for dimensionality reduction, but also as a means of validating the latent structure of reputational constructs and verifying measurement models. A conceptual framework for an integrative model is proposed, uniting three levels of reputational data - media-level (presence and tonality indices), cognitive-level (stakeholder assessments of company attributes), and behavioural-level (audience and partner responses). The findings obtained expand the methodological apparatus of media research and establish a theoretical foundation for designing valid, comprehensive tools for monitoring and managing reputation in a digital media environment.

Authors

Institutions

Publication Details

Journal
Litera
Published
2026-04-01
DOI
https://doi.org/10.25136/2409-8698.2026.4.78934
Primary Topic
Corporate Identity and Reputation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Index modeling and factor analysis in media studies

Andrey Viktorovich Yablonskih
Litera
Corporate Identity and Reputation
article

Index modeling and factor analysis in media studies

Andrey Viktorovich Yablonskih
article en

Abstract

The subject of this article is the methodological foundations for applying index modelling and factor analysis to the measurement of reputation in digital media communications. The article addresses the problem of constructing valid measurement models that reflect the multidimensional nature of reputation as a media-communicative construct. The focus of analysis lies on the principles of constructing and aggregating mediametric indices, as well as the mechanisms for aligning them with stakeholder perception models. A particular emphasis is placed on examining the compatibility of both quantitative media indicators and qualitative audience assessments within a unified measurement space. Special attention is devoted to the methodological capabilities of factor analysis as a tool for identifying latent reputational factors and verifying the internal consistency of measurement constructs in the context of growing volumes of media data and increasing complexity of the digital communication environment. The methodological basis of the research comprises systemic and structural-functional approaches, enabling the interpretation of reputation as a hierarchically organised aggregate of interrelated parameters. Methods of comparative and conceptual analysis are employed for the typologisation of index models. The key instrument is factor analysis, applied to identify latent variables and verify the structural validity of models. The scientific novelty of the research consists in developing the conceptual foundations for integrating mediametric indices and stakeholder perception models into a unified index architecture for measuring reputation. For the first time, the thesis is substantiated that the isolated application of mediametric and perceptual approaches generates methodological limitations: the incomparability of data of different natures and the fragmentation of interpretive conclusions, which prevents obtaining a holistic picture of an organisation's reputational state. The methodological status of factor analysis in reputational research has been refined: it is considered not only as a tool for dimensionality reduction, but also as a means of validating the latent structure of reputational constructs and verifying measurement models. A conceptual framework for an integrative model is proposed, uniting three levels of reputational data - media-level (presence and tonality indices), cognitive-level (stakeholder assessments of company attributes), and behavioural-level (audience and partner responses). The findings obtained expand the methodological apparatus of media research and establish a theoretical foundation for designing valid, comprehensive tools for monitoring and managing reputation in a digital media environment.

Litera(4)
Odesa I. I. Mechnikov National University (UA)
Openalex Percentile: Top 26%
Corporate Identity and Reputation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.