This is a curated compilation that merges the following 13 distinct research datasets to deliver unparalleled insights into the domain of Gambling and iGaming promotions:
- 3718 Gambling/iGaming Telegram Channels;
- 1007 Gambling/iGaming Discord Servers;
- 98 Gambling/iGaming Forums;
- 329 Gaming & iGaming Marketing Agencies;
- 819 Gambling/iGaming Media Outlets;
- 1315 Gambling/iGaming Rating Websites;
- 2461 Gambling/iGaming Instagram Accounts;
- 1666 iGaming-related Facebook Accounts (1097 groups, 569 personal accounts);
- 126 Gambling/iGaming Reddit Communities (with optimal posting times);
- 2718 Gambling/iGaming YouTube Channels (with contact details);
- 2505 Gambling/iGaming Twitch Channels;
- 977 Gambling/iGaming TikTok Accounts;
- 2152 iGaming-Related Twitter Accounts (for a comprehensive social media overview).
Research Goals and Objectives
- Collect and categorize forums, Telegram and YouTube channels, Discord servers, Reddit communities, as well as Facebook, Instagram, Twitch, TikTok, and Twitter accounts pertaining to gambling topics;
- Gain a holistic understanding of the digital landscape surrounding gambling by aggregating and categorizing various platforms;
- Provide an insightful analysis of the platforms' reach and resonance, facilitating better decision-making for industry stakeholders.
Data Collection Methods:
- Open Google search;
- Platforms’ internal search (e.g., Telegram channel search, Discord server search, Reddit community search, etc.);
- Platform collection via other social media (YouTube, Twitter, Instagram, Twitch, TikTok, Facebook);
- Social media data processing (YouTube, Twitter, Telegram, Discord, Instagram, Twitch, TikTok, Reddit, and Facebook);
- Service-specific searches (Crunchbase, Owler, LinkedIn);
- HugoMoe’s service for checking Discord channel creation dates;
- SimilarWeb’s service for evaluating website traffic;
- Social Blade for evaluating account/channel popularity;
- Streams Charts for Twitch account popularity estimation;
- Social Rise service for determining the best time for social media publications.
- Total Grade (SB Rank) — represents an account’s/channel's rating compared to the rest of the database (used for Instagram, Facebook, YouTube, Twitch, TikTok, and Twitter);
- Engagement Rate (ER) — a metric based on a particular account's 16 latest images according to public APIs (used for Instagram);
- Likes Rank — top chart position based on cumulative number of likes (used for Facebook and YouTube);
- Channel Data Quality — an estimation based on Average Viewers and stream numbers (used for Twitch).
The information collected in this study includes various channels, servers, forums, marketing agencies, media sources, rating websites, and accounts that participate in the formation of the gambling community. It is important to note that this study did not exclusively focus on collecting gambling-only entities, but rather encompasses a diverse range of bloggers, streamers, communities, and platforms associated with gambling-related activities. The information presented in this study does not claim absolute completeness, as it represents an intermediate stage in the planned research cycle. The inclusion of these entities does not imply an endorsement or validation of their content, actions, or affiliations.
For visualization convenience, certain data points have been averaged and categorized as follows:
- "<10k" — accounts with less than 10,000 followers;
- "10k - 100k" — accounts with over 10,000 but less than 100,000 followers;
- "100k - 1m" — accounts with over 100,000 but less than 1,000,000 followers;
- ">1m" — accounts with over 1,000,000 followers.
Total Grade Values:
- "TBD" — the grade has not yet been determined;
- "D" — concatenates Total Grades with the following values: D+, D.;
- "C" — concatenates Total Grades with the following values: C+, C, C-;
- "B" — concatenates Total Grades with the following values: B+, B, B-;
- "A" — concatenates Total Grades with the following values: A++, A+, A, A-.
- "<1k" — accounts with less than 1,000 likes;
- "1k - 10k" — accounts with over 1,000 but less than 10,000 likes;
- "10k - 100k" — accounts with over 10,000 but less than 100,000 likes;
- "100k - 1m" — accounts with over 100,000 but less than 1,000,000 likes;
- ">1m" — accounts with over 1,000,000 likes.
- "<100" — accounts with less than 100 uploads;
- "100 - 500" — accounts with over 100 but less than 500 uploads;
- "500 - 1k" — accounts with over 500 but less than 1,000 uploads;
- ">1k" — accounts with over 1,000 uploads.
- "<10k" — websites with less than 10,000 visits;
- "10k - 100k" — websites with over 10,000 but less than 100,000 visits;
- "100k - 1m" — websites with over 100,000 but less than 1,000,000 visits;
- ">1m" — websites with over 1,000,000 visits.
- "<1m" — channels with less than 1 million views;
- "1m - 10m" — channels with between 1 and 10 million views;
- "10m - 100m" — channels with between 10 and 100 million views;
- "100m - 1b" — channels with between 100 million and 1 billion views;
- ">1b" — channels with over 1 billion views.
- "<10k" — channels with less than 10,000 subscribers;
- "10k - 100k" — channels with over 10,000 but less than 100,000 subscribers;
- "100k - 1m" — channels with over 100,000 but less than 1,000,000 subscribers;
- ">1m" — channels with over 1,000,000 subscribers.
Additional insights and labels used in this study:
- "DM" — stands for “Direct Messages” and refers to the option of sending private messages within a particular platform;
- Various accounts, communities, and channels were excluded or banned during data collection due to non-compliance or other reasons, which may impact the final dataset and calculations therein.
The study conducted an extensive analysis of various online platforms associated with gambling, including Telegram, Discord, forums, marketing agencies, media outlets, rating websites, Instagram, Facebook, Reddit, YouTube, Twitch, TikTok, and Twitter. The data was categorized and sorted into different groups for each platform, revealing insights into their characteristics and audience engagement.
See below for the summarized conclusions per individual platform:
- A dataset of 3718 gambling-associated Telegram accounts was formed;
- Accounts were grouped by followers, languages, and type.
- A dataset of 1007 gambling-associated Discord servers was formed;
- Servers were grouped by followers and creation date.
- A dataset of 98 gambling-associated forums was formed;
- Forums were categorized by type and traffic, and can additionally be sorted to represent a chart of top forums by traffic.
- A dataset of 329 gambling and gaming-associated marketing agencies was formed;
- Agencies were grouped by field of activity and influencer affiliations;
- Top agencies by traffic and the oldest agencies by foundation year were additionally identified.
- A dataset of 819 gambling-associated media sources was formed;
- Media sources were categorized by traffic and associated tags.
- A dataset of 1315 gambling-associated rating websites was formed;
- Rating websites were grouped by traffic and associated tags;
- A heat table showcasing the ratio of websites based on tag and visitors was added.
- A dataset of 2461 gambling-associated Instagram accounts was formed;
- Accounts were grouped by follower numbers, total grade, engagement rate, AVG comments, AVG likes, and contact options.
- A dataset of 1666 gambling-associated Facebook accounts was formed;
- Accounts were grouped by follower numbers, total grade, likes rank, type, and contact options.
- A dataset of 126 gambling-associated Reddit communities was formed;
- Communities were grouped by follower numbers and best time to publish.
- A dataset of 2718 gambling-associated YouTube channels was formed;
- Channels were grouped by subscriber counts, video views, country, gambling content, total grade, and channel type.
- A dataset of 2505 gambling-associated Twitch accounts was formed;
- Accounts were grouped by follower numbers, channel data quality, top category by HW, active days, airtime hours, hours watched, and language;
- Separate reports were provided for Dominant Gambling, Partial Gambling, and Undetermined categories.
- A dataset of 977 gambling-associated TikTok accounts was formed;
- Accounts were grouped by follower numbers, total grade, uploads, likes, and content.
- A dataset of 2251 gambling-associated Twitter accounts was formed;
- Accounts were grouped by follower numbers, total grade, likes, tweets, and contact options;
Each platform's data was carefully analyzed and grouped to provide insights into follower distribution, user engagement, content quality, and other relevant metrics. The study's conclusions offer valuable information for understanding the landscape of gambling-associated content across different online platforms.
Future Goals and Extensions
- Search for account contact details;
- Search for advanced user engagement metrics;
- Account activity field categorization;
- Analysis of marketing trends and promotional flyers;
- Identification of regional affiliations;
- Showcase of advertising pricing models;
- Expansion of the general account list, as well as regional lists for Asia & Pacific, MENA.
The listed and other additions will be added in planned expansions and subsequent research cycles.
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