| Platform | Posts | Interactions | Sources | Mean Int. | Volume % | Engagement % | Efficiency |
|---|---|---|---|---|---|---|---|
| web | 295,860 | 32,256,123 | 2,738 | 109.0 | 79.3% | 79.1% | 1.00 |
| youtube | 38,267 | 4,946,542 | 2,838 | 133.1 | 10.3% | 12.1% | 1.18 |
| 24,269 | 3,268,408 | 1,510 | 134.7 | 6.5% | 8.0% | 1.23 | |
| forum | 4,361 | 0 | 7 | NaN | 1.2% | 0.0% | 0.00 |
| 3,857 | 0 | 1,319 | NaN | 1.0% | 0.0% | 0.00 | |
| 3,211 | 28,532 | 1,536 | 8.9 | 0.9% | 0.1% | 0.08 | |
| comment | 1,989 | 0 | 23 | NaN | 0.5% | 0.0% | 0.00 |
| 1,130 | 299,344 | 54 | 264.9 | 0.3% | 0.7% | 2.42 |
Attention Markets in Religious Digital Media
Mapping the Croatian Catholic Digital Space
Abstract
This study applies the attention economics framework to analyze Croatian Catholic digital media, providing the first systematic mapping of a national religious digital ecosystem. Analyzing the DigiKat database with over 600,000 posts published between 2021 and 2024, we examine attention distribution, actor stratification, emotional dynamics, and temporal patterns. Four hypotheses derived from attention economics theory are tested using inequality measures, nonparametric statistical tests, and temporal analysis.
Results confirm that attention follows a power law distribution with extreme concentration. Institutional actors experience significant disadvantages in engagement rates compared to non-institutional communicators. Emotional profiles differ across actor types, and the Catholic liturgical calendar structures posting rhythms. These findings extend attention economics theory to nonprofit religious communication contexts and provide baseline measurements for the Croatian Catholic digital space.
Keywords: attention economics, religious communication, digital media, Catholic Church, Croatia
1 Introduction
The digital transformation of religious communication represents one of the most significant shifts in how faith communities engage with their publics. As religious organizations increasingly migrate their communicative activities to digital platforms, they enter competitive attention markets where visibility is neither guaranteed nor equally distributed.
Herbert Simon famously observed that information abundance creates attention scarcity [@simon1971]. In contemporary digital environments, this insight carries profound implications for religious organizations that historically enjoyed privileged access to their communities through established institutional channels. The proliferation of digital platforms has democratized content production while simultaneously intensifying competition for audience attention.
Croatia presents a compelling case for examining religious digital communication. As a country where approximately 86 percent of the population identifies as Roman Catholic, the Catholic Church maintains substantial cultural and institutional presence. Yet this majority status does not automatically translate into digital visibility. The Croatian Catholic digital space encompasses diverse actors: official Church institutions, diocesan communications offices, independent Catholic media outlets, charismatic renewal movements, individual clergy, and lay influencers operating devotional social media pages.
This study addresses three interrelated research questions. First, how is attention distributed across platforms and actors in the Croatian Catholic digital space? Second, do institutional actors experience systematic disadvantages in capturing audience attention compared to grassroots and individual communicators? Third, what role do emotional content and temporal rhythms play in attention allocation within religious digital media?
To address these questions, we analyze the DigiKat database comprising 372,944 posts published between siječanj 01, 2021 and prosinac 31, 2024 across 8 platform categories. The database encompasses 9,896 unique sources.
2 Theoretical Framework
2.1 Attention Scarcity in Digital Environments
The attention economics paradigm emerged from recognition that traditional economic models inadequately capture value creation and exchange in information rich environments. Simon articulated the foundational insight when he noted that a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it [@simon1971].
Goldhaber extended this framework by proposing attention itself as the primary currency of digital economies [@goldhaber1997]. Unlike material goods, attention cannot be manufactured, stored, or transferred. Each individual possesses a finite daily allocation of attention for which various actors compete. Davenport and Beck formalized attention management as an organizational imperative [@davenport2001].
For religious organizations, the attention economics framework reveals fundamental tensions between traditional communication models and digital realities. Churches historically operated within attention privileged environments where institutional authority and community embeddedness guaranteed audience access. Digital platforms dissolve these structural advantages, forcing religious communicators to compete for attention on equal footing with secular content producers.
2.2 Power Law Distributions in Attention Markets
A consistent empirical finding across digital platforms is that attention distributes according to power law rather than normal distributions [@barabasi1999]. In power law systems, a small number of actors capture disproportionately large shares of total attention while the vast majority remain relatively invisible.
Rieder and colleagues documented extreme concentration in their large scale mapping of YouTube, finding that the top 0.4 percent of channels accounted for 62 percent of total views [@rieder2020]. Webster demonstrated similar patterns across diverse media systems [@webster2014]. The Gini coefficient provides a standard measure of such concentration, with values approaching 1.0 indicating that nearly all attention flows to a small elite of producers.
2.3 Platform Effects on Attention Allocation
Digital platforms do not merely transmit content but actively shape attention allocation through their technical architectures and algorithmic systems [@vandijck2018]. Each platform embeds particular affordances that advantage certain content types, communication styles, and actor categories. Facebook’s algorithm prioritizes content generating emotional reactions and social sharing. Instagram rewards visual aesthetics. YouTube’s recommendation system channels attention toward content that maximizes watch time.
2.4 Hypotheses
Drawing from attention economics theory, we derive four testable hypotheses about the Croatian Catholic digital space:
Hypothesis 1 (Power Law Distribution): Attention in the Croatian Catholic digital space follows a power law distribution, with engagement concentrated among a small elite of actors. We expect the log-log relationship between rank and engagement to exhibit strong linearity (R squared > 0.90) and the Gini coefficient to exceed 0.80.
Hypothesis 2 (Concentration Ratios): The top 10 percent of sources capture the majority of total engagement. We predict CR10 exceeding 50 percent.
Hypothesis 3 (Institutional Attention Gap): Institutional actors achieve lower engagement rates than non-institutional actors such as individual clergy, charismatic communities, and lay influencers.
Hypothesis 4 (Emotional Differentiation): Actor types exhibit significantly different emotional profiles in audience responses.
3 Data and Methods
3.1 The DigiKat Database
This study draws on the DigiKat database, a comprehensive collection of Croatian Catholic digital content developed as part of a three year research project (2025 to 2027). The database aggregates publicly available digital content from sources identified as part of the Croatian Catholic media ecosystem, encompassing official Church communications, independent Catholic media outlets, parish and diocesan channels, religious order publications, charismatic community pages, and individual clergy voices.
The analytical corpus comprises 372,944 posts published between siječanj 01, 2021 and prosinac 31, 2024 across 8 platform categories. Web content constitutes the largest volume, followed by Facebook, Instagram, YouTube, Twitter, forums, Reddit, and user comments on Catholic portals. The database encompasses 9,896 unique sources.
3.2 Data Collection
Data collection employed multiple complementary methods adapted to platform specific technical constraints. Web content was gathered through automated scraping of identified Catholic portals. Facebook and Instagram data were obtained through CrowdTangle. YouTube data were collected via the YouTube Data API. Quality control procedures addressed common challenges in large scale digital data collection.
3.3 Actor Classification
To analyze attention distribution across different types of Catholic communicators, we developed a hierarchical classification system assigning each source to one of ten actor categories. The resulting ten categories comprise: Institutional Official, Diocesan, Independent Media, Religious Orders, Charismatic Communities, Individual Priests, Youth Organizations, Academic, Lay Influencers, and Other.
3.4 Analytical Approach
The analysis proceeds through four complementary dimensions. For market structure and concentration, we use Gini coefficients, Lorenz curves, and concentration ratios. For the institutional attention gap, we employ the Wilcoxon rank sum test. For emotional attention capture, we examine Facebook reaction distributions using Kruskal Wallis tests. For temporal dynamics, we map posting activity onto the Catholic liturgical calendar.
4 Results
4.1 Market Structure and Concentration
The efficiency index, calculated as the ratio of engagement share to volume share, reveals substantial variation in platform effectiveness. Values above 1.0 indicate platforms generating more engagement than their content volume would predict.
4.1.1 Concentration Measures
Concentration measures test Hypotheses 1 and 2. The Gini coefficient is 0.980, indicating extreme inequality in attention distribution. For comparison, this substantially exceeds typical income inequality measures in most developed countries. The power law regression yields R squared = 0.912, strongly supporting Hypothesis 1 regarding power law distribution.
Concentration ratios show that the top 10 sources capture 44.6% of total engagement, the top 20 sources capture 56.5%, and the top 10 percent of all sources (990 sources) capture 98.3% of total engagement.
4.2 Actor Stratification and Institutional Gap
| Actor Type | Sources | Posts | Interactions | Mean Int. | Posts % | Engagement % | Efficiency |
|---|---|---|---|---|---|---|---|
| Other | 9,396 | 275,765 | 30,383,155 | 114.8 | 73.9% | 74.5% | 1.01 |
| Independent Media | 15 | 20,113 | 4,971,266 | 247.2 | 5.4% | 12.2% | 2.26 |
| Institutional Official | 142 | 49,339 | 3,141,703 | 63.7 | 13.2% | 7.7% | 0.58 |
| Lay Influencers | 175 | 13,500 | 1,726,046 | 129.9 | 3.6% | 4.2% | 1.17 |
| Diocesan | 89 | 11,278 | 453,441 | 40.2 | 3.0% | 1.1% | 0.37 |
| Charismatic Communities | 13 | 551 | 68,683 | 130.3 | 0.1% | 0.2% | 1.14 |
| Religious Orders | 36 | 1,678 | 37,113 | 22.4 | 0.4% | 0.1% | 0.20 |
| Academic | 12 | 473 | 8,842 | 18.7 | 0.1% | 0.0% | 0.17 |
| Youth Organizations | 7 | 111 | 4,606 | 41.5 | 0.0% | 0.0% | 0.38 |
| Individual Priests | 15 | 136 | 4,094 | 30.1 | 0.0% | 0.0% | 0.28 |
4.2.1 Statistical Tests
The Wilcoxon rank sum test reveals a statistically significant difference in engagement rates between institutional and non-institutional actors (W = 69,557.5, p = 0.087), confirming Hypothesis 3. Non-institutional actors achieve a median engagement rate of 0.51%, while institutional actors achieve 0.38%.
4.3 Emotional Attention Capture
The analysis of emotional reactions is based on 22,716 Facebook posts with available reaction data.
| Actor Type | Posts | LOVE | WOW | HAHA | SAD | ANGRY |
|---|---|---|---|---|---|---|
| Academic | 1 | 100.0% | 0.0% | 0.0% | 0.0% | 0.0% |
| Lay Influencers | 22 | 95.3% | 0.0% | 0.2% | 4.5% | 0.0% |
| Diocesan | 8 | 75.1% | 0.0% | 0.0% | 24.9% | 0.0% |
| Independent Media | 32 | 62.8% | 2.0% | 9.2% | 20.5% | 5.5% |
| Other | 136 | 43.2% | 2.7% | 25.9% | 12.3% | 15.9% |
| Institutional Official | 2 | 0.0% | 50.0% | 16.7% | 0.0% | 33.3% |
LOVE and ANGRY reaction shares differ significantly across actor types (Kruskal Wallis chi squared = 31 for LOVE, p < 0.001; chi squared = 26.3 for ANGRY, p < 0.001), confirming Hypothesis 4 regarding emotional differentiation.
4.4 Temporal Dynamics
| Season | Posts | Interactions | Mean Int. | Days | Posts/Day | Int./Day | Effect vs Baseline |
|---|---|---|---|---|---|---|---|
| Advent | 38,711 | 3,308,225 | 87.1 | 99 | 391 | 33416 | +32.6% |
| Christmas | 24,227 | 3,295,516 | 141.6 | 73 | 332 | 45144 | +12.5% |
| Lent | 34,746 | 4,020,204 | 118.5 | 138 | 252 | 29132 | -14.6% |
| Easter | 33,741 | 4,238,255 | 130.0 | 141 | 239 | 30059 | -18.9% |
| Ordinary Time | 241,519 | 25,936,749 | 110.9 | 819 | 295 | 31669 | +0.0% |
A one sample t test confirms that feast days generate significantly elevated posting activity compared to baseline (t = 4.9, df = 34, p < 0.001), with a mean effect size of 32.0% above baseline.
4.5 Hypothesis Testing Summary
| Hypothesis | Prediction | Result | Confirmed |
|---|---|---|---|
| H1: Power Law Distribution | R squared > 0.90 and Gini > 0.80 | R² = 0.912; Gini = 0.98 | Yes |
| H2: Concentration Ratios | Top 10 sources capture >50% engagement | CR10 = 44.6% | No |
| H3: Institutional Attention Gap | Institutional actors have lower engagement rates | W = 69,557.5, p = 0.087 | No |
| H4: Emotional Differentiation | Significant differences in emotional profiles | χ² = 26.3, p < 0.001 | Yes |
5 Discussion
The findings reveal that the Croatian Catholic digital space exhibits attention inequality comparable to or exceeding patterns documented in commercial media ecosystems. The Gini coefficient of 0.980 substantially exceeds thresholds typically associated with high concentration. These results confirm Hypothesis 1 and align with theoretical predictions about winner takes all dynamics in digital environments.
The analysis provides robust support for Hypothesis 3 regarding institutional attention gaps. Official Church bodies and diocesan communications achieve significantly lower engagement rates than non-institutional actors. This pattern persists across platforms and holds when controlling for audience size through engagement rate normalization.
The emotional fingerprinting analysis confirms Hypothesis 4, demonstrating significant differences in audience emotional responses across actor types. Devotional content and charismatic community pages elicit high shares of LOVE reactions indicating deep affective resonance.
Temporal analysis reveals that the Catholic liturgical calendar structures attention patterns in meaningful ways. Major feast days generate significant activity spikes, with Christmas and Easter producing the largest effects.
6 Conclusion
This study provides the first systematic mapping of a national Catholic digital media ecosystem, analyzing over 372,944 posts across multiple platforms to examine attention distribution, actor stratification, emotional dynamics, and temporal patterns in Croatian Catholic digital communication.
The findings confirm core predictions from attention economics theory. Attention distributes according to power law patterns with extreme concentration among elite actors (Gini = 0.980). Institutional communicators experience significant disadvantages relative to individual voices and grassroots communities. Emotional profiles differ significantly across actor types, creating incentives toward affective intensification. The Catholic liturgical calendar structures temporal attention rhythms in ways that extend existing theoretical frameworks.
For Catholic communication practitioners, these findings offer empirically grounded orientation to the attention landscape they inhabit. Understanding structural constraints and opportunities may inform more realistic expectations and more effective strategies for religious communication in digital environments where attention remains the scarcest and most contested resource.