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TOP casinos in popularity on Google and social networks
Introduction: Why Measure "Popularity"
Popularity is not "better" or "worse," it is the scale of audience interest in the here and now. She helps:- players - to understand which brands really choose and discuss;
- content creators - prioritize reviews;
- operators - to see the market, benchmarks and dynamics.
To avoid noise, we separate search demand (Google) and social engagement (YouTube/TikTok/Instagram/X/Telegram/Reddit/Discord) and combine them into a single assessment with anti-fraud filters.
Data sources (no brands - categories only)
Google (organic, not advertising)
Branded Search Volume (BSV): monthly volume of branded searches and their trend.
Google Trends Index (GTI): Relative momentum over 30/90/365 days.
Related/Autosuggest Signals: brand + bonus/output/feedback frequencies, etc.
Share of Search (SoS): brand share of total category brand searches in the market/language.
Social networks (quality of involvement, not "naked subscribers")
ERpost/ERview: engagement on post/per 1000 views.
View Velocity: the speed of gaining views in the first 24/72 hours (video platforms).
Growth Rate: 30/90 day audience growth (net, no bots)
Share of Voice (SoV): Proportion of mentions/discussions in thematic communities.
Sentiment Balance: positive/negative ratio in discussions (normalized from the "noise" of stocks/draws).
Anti-cheating and data cleaning
To ensure that the rating reflects real interest, we apply filters:1. Bots deduplication: peak detectors, correlation of subscriptions with ER, sharp "night" bursts.
2. Payday cut-off: ER anomalies in draws/" bonus subscription."
3. Negative hype: a surge in searches due to scandal/blocking is marked and partially "fined."
4. Multi-accounts and grids: recurring comment/emoji/copy-paste patterns.
5. Geo-normalization: we take into account the population/Internet penetration so that "small markets" are not lost.
Weighting and summary score
Final Population Score (0-100) = 0. 55 × Google + 0. 45 × Social networks, where: Google (internal subscore, 0-100):- 30% - Share of Search (SoS, 90 days)
- 25% - BSV trend (MoM/YoY, smoothing)
- 25% - GTI (30/90/365 days, with a freshness weight of 0. 5/0. 3/0. 2)
- 10% - "brand + trust requests" (output/reviews/license) - as "quality of interest"
- 10% stability (low spike variance = plus)
- 30% - ERpost/ERview (platform average)
- 25% - View Velocity (first 24/72 hours)
- 20% - Growth Rate (30/90 days, net gain)
- 15% - SoV in thematic communities (forums/chats/subreddits)
- 10% - Sentiment Balance (adjusted for negative hype)
Freshness ratios: last 30 days × 1. 3, 90 days × 1. 1, year × 0. 9.
Fines: suspicious peaks/bot gain/unnatural ER lower the result by 5-25 percentage points. depending on the severity.
Rating classes and interpretation
S (90-100): Explosive but sustained interest; strong SoS and healthy ER, no markups; multiplatform.
A (80-89): Stable growth; social attraction above average; regular organic peaks.
B (70-79): Good in 1-2 channels, average in the rest; growth potential.
C (60-69): Local or niche popularity; high dependence on stocks/draws.
D (<60): Weak interest or "artificial life"; ER/SoV do not support subscriptions.
Regional slices and how to read them
By country/language: we build separate SoS/SoV. Brand can be S in LatAm and B in the EU - this is the norm.
By platform: strong YouTube + weak TikTok ≠ bad if the audience core is "long video."
By time: seasonality (holidays, sports events) affects GTI/ER - we use 30/90/365 windows to see both outbreaks and the long-term trend.
How the card is formed in the TOP list
In each card we show:- Class (S-D) and Population Score (integer 0-100);
- Google block: SoS, GTI 30/90/365, BSV trend;
- Social block: ER/Velocity/Growth/SoV/Sentiment by key platforms;
- Strengths: where exactly the brand "pulls" (e.g. YouTube long-form, Reddit discussions);
- Growth zones: "weak TikTok," "low SoV in Telegram," "volatile sentiment";
- Seasonality: notes on spikes (major tournaments, promotional campaigns).
Frequent distortions and how we level them
1. Purchased subscriptions: normalization by ER and velocity; "dead" subscribers are reset to zero.
2. Draws: peak posts are marked, reduce their contribution to ER/Growth.
3. Crisis hype: a surge in negativity in search/comments does not convert to a high Score (sentiment penalty).
4. Local locks/filters: shift focus to available sites and adjust SoS.
5. Subtle brands-renaming: we combine aliases/typos, otherwise the trend "breaks."
Mini checklist for player
1. See the class and dynamics of 90 days: is interest growing without a "saw."
2. Check SoS against ER: high search and low engagement = likely promotional "pumping."
3. Check sentiment: popularity on the negative is a wake-up call.
4. See the regional cut: the brand may not be popular in your country.
5. Don't confuse popularity with security: combine with payout/license/payment ratings.
For operators: how to honestly increase popularity
Content portfolio: mix long-form (YouTube) + short-form (TikTok/Reels) + community (Telegram/Reddit/Discord).
Value-first promo: transparent stock rules, less "lottery" - above stable ER.
Community management: regular AMAs, streams with Q&A, feedback in release notes.
Seasonal packages: sports/holiday content maps; tracking velocity in the first 24/72 hours.
Reputation: quick responses to public complaints, post-mortems of incidents - reduce negative hype.
Rating update and transparency
Frequency: weekly - dashboards 7/30 days; monthly - "big" summary 90/365.
The methodology is open: weights, windows, fines are fixed; changes are versioned.
Trace audit: save aggregated raw metrics and cleaning masks (without personal data).
FAQ (short)
Why did a brand with a small number of subscribers fall into class A?
High ER/Velocity + strong SoS: the audience is small, but "lively" and involved.
Why has popularity fallen for no apparent reason?
Season/campaign ended; see 90/365 windows - if the long-term trend is flat, this is not a problem.
Is it possible to "take off" in a month?
Yes, but it's harder to keep. We fine one-time bursts without sustained ER/SoV.
How to compare markets with each other?
See normalized SoS and regional classes - direct comparison of different countries without normalization is incorrect.
The rating for popularity on Google and social networks is a thermometer of interest, not a verdict on quality. It shows where the brand is trusted with attention and timing. Read the class, dynamics and balance between search and engagement - and use this layer paired with ratings of reliability, payments and local payments to make adult, informed decisions.