The problem of measuring reputation in the context of digital media communications
Bibliographic Data
| ID | 22150436 |
|---|---|
| Authors | Andrey Viktorovich Yablonskikh (0000-0001-7821-6563, Odesa I. I. Mechnikov National University, corresponding author) |
| Year | 2026 |
| Issue | 5 |
| Pages | 240-255 |
| Publication date | 2026-05-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Филология научные исследования (JOURNAL) |
| Journal identifiers | ISSN: 2454-0749 • E-ISSN: 2454-0749 |
| Publisher | Aurora Group, s.r.o (PUBLISHER) |
| DOI | 10.7256/2454-0749.2026.5.78918 |
| OpenAlex | W7163131656 |
| Language | EN |
| References cited | 27 |
The subject of this study is the problem of organizational reputation measurability in the context of digital media communications, characterized by highly dynamic information flows, audience fragmentation, and the algorithmization of content distribution. Reputation is considered as a complex media communication construct, formed through the interaction of an organization with various stakeholder groups in the digital public space and reflecting an aggregate of evaluations, interpretations, and discursive practices. Within the framework of this study, particular attention is given to analyzing the limitations of existing approaches to reputation measurement, which are predominantly based on quantitative metrics of digital monitoring. Such aspects as the representativeness of social platform data, their authenticity in the context of widespread manipulative practices, and the problem of cross-platform comparability of reputational indicators are examined. Additionally, the subject of the study encompasses the transformation of reputation analysis tools under the influence of digitalization, the development of big data and artificial intelligence technologies, as well as the changing logic of reputation formation within a platform-based media environment. The methodological framework comprises a systems approach, comparative analysis, and content analysis. Drawing on a review of specialized literature (Scopus, WoS, eLibrary), the definition of "online reputation measurability" has been refined, and a systematization of key metrics has been conducted – including sentiment index, reach, engagement, share of voice, response speed, and composite indices (RepTrak, MediaIndex, NPS). The scientific novelty of the study lies in the refinement and systematization of methodological limitations of reputation measurement in the context of digital media communications, taking into account the specifics of the platform environment and algorithmic content selection. In contrast to approaches primarily focused on quantitative indicators, the study substantiates the necessity of treating reputation as a multidimensional media communication construct, shaped by the cumulative impact of communication practices, discursive interpretations, and technological factors. Key limitations of existing methods have been identified, including the problems of digital data representativeness, authenticity, algorithmic bias, as well as cross-platform and temporal incomparability of indicators. As the principal conclusion, the study substantiates the need to develop integrative reputation measurement models that combine big data analysis methods with qualitative approaches, including discourse analysis and expert interpretation. The promising potential of transitioning to predictive reputation management models based on early signal analysis and media process dynamics is emphasized, which enhances the effectiveness of strategic management in the digital environment
Comparability · Digital media · Representativeness heuristic · Reputation · Social media · Stakeholder · Corporate Identity and Reputation · Digital Marketing and Social Media · Security, Politics, and Digital Transformation
| Citation velocity | historical |
|---|---|
| Highly cited | No |