Channels

Channels are the core content of Verychat, serving as a community platform where influencers share information and users with common interests can converse. Through this, users can communicate and int

Maximum Number of Users per Channel

Initially, each channel can recruit up to 200,000 subscribers. Later, plans are in place to upgrade server specifications and expand the subscriber limit to unlimited.

Channel Features

• Permissions: Channel owners (Admins) can appoint managers to co-manage the channel. Only the Admin has the authority to delete the channel.

• Member Levels: Channel owners can assign levels to subscribers and active users, creating tiered benefits.

• Announcements: Important messages can be pinned at the top of the channel using the pin

• Global Push Notifications Channel owners can send important messages to subscribers once a day using the @everyone mention. This feature sends messages bypassing individual notification settings.

• Airdrops: Channel owners can airdrop $VERY coins from their wallets to channel subscribers.

• Entry for Specific NFT/Token Holders: Entry can be restricted to users who own specific NFTs or tokens.

• Staking All holders of $VERY coins must designate a subscribed channel to stake their $VERY.

Recommended Channels

Verychat has implemented a recommended channel algorithm to motivate channel owners and help them grow as content providers.

When a feed posted by a channel owner becomes a popular post, that channel becomes a recommended channel, visible to most users on Verychat, thanks to the algorithm. This exposure extends even to users who speak different languages, thus increasing visibility among global users. Communication with global users is facilitated through Verychat's on-device AI translation. You can think of the recommended channel algorithm as similar to YouTube's "home page" or Instagram's "explore tab."

Channel Recommendation Algorithm

The recommendation score 𝑅 is calculated as the weighted sum of various factors.

$$R=w 1 ​ ×E+w 2 ​ ×M+w 3 ​ ×U$$

• E is the Engagement Score.

• M is the Content Metadata Score.

• U is the User-Channel Interaction Score.

• w1, w2, w3 are the weights for each respective factor.

Engagement Score, 𝐸

$$E=w e1 ​ ×LI+w e2 ​ ×V+w e3 ​ ×S$$

• LI is the Likes

• V is the Views

• S is the Shares

• we1, we2, we3​ are the weights for each respective factor.

Content Metadata Score, 𝑀

$$M=w m1 ​ ×K+w m2 ​ ×D+w m3 ​ ×C$$

• K represents Keyword Match - the degree of alignment between user interests and content keywords.

• D stands for Description Match - the quality of the content description and its relevance to keywords.

• C is for Content Relevance - the trendiness and relevance of the content topic.

• wm1, wm2, wm3 are the weights for each respective factor.

User-Channel Interaction Score, 𝑈

$$U=w u1 ​ ×H+w u2 ​ ×SU+w u3 ​ ×A$$

• H represents View History - the number of times a user has viewed content from the channel previously.

• SU stands for Subscription - whether the user is subscribed to the channel.

• A denotes Activity - how frequently a user engages with the channel (e.g., participating in discussions, liking posts).

• wu1, wu2, wu3 are the weights for each respective factor.