NFT Social Volume
Definition
Social Volume is build on top of the Social Data. The idea is pretty much the same as for Social Volume.
The total number of text documents that
contain the mention of certain NFT Collection at least one. Examples of documents are telegram
messages and reddit posts. E.g., if a single short telegram message includes the word
bored ape
more than once, this message will increase the social volume of the
Bored Ape Yacht Club by 1. If a long reddit post contains the word bored ape
10 times,
this again will increase the social volume of the Bored Ape Yacht Club by 1.
Social Volume computed for NFT contract. For each contract we construct a special search term. We use machine learning model based on TF-IDF for computing those search terms. The idea is that we try to compute search terms based on pairwise similarity of NFTs' names. For computing embedding per each collections' name we use TF-IDF model on n-grams of chars.
Some search terms examples for some NFT collections:
- CryptoPunks -
cryptopunks
; - Veefriends Series 2 -
veefriends
; - CyberKongz VX -
cyberkongz
.
Please note that metrics may undergo changes in historical values due to automated recalculations triggered monthly. We constantly update our labels which helps us to keep labels as fresh as possible but result historical data changes. Any modifications to labels, social sources, or relevant jobs will prompt recalculation for the previous month's data. Within a 12 hour period, metric can be supplemented with new data.
Access
Measuring Unit
Amount of documents that mention the given NFT Collection.
Data Type
Change Metrics
Frequency
Latency
Sanbase
NFT Social Volume from all sources for a spicific NFT contract can be seen on a charts page.
The combined social volume from all sources is displayed.
SanAPI
Available under the nft_social_volume
name, where the value is combined from all sources (telegram, reddit, twitter, bitcointalk).
Social Volume for Azuki
1 2 3 4 5 6 7 8 9 10 11 12 13
{ getMetric(metric: "nft_social_volume") { timeseriesData( selector: {contractAddress:"0xed5af388653567af2f388e6224dc7c4b3241c544"} from: "2022-01-01T00:00:00Z" to: "2022-03-07T00:00:00Z" interval: "1d" ) { datetime value } } }
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