REx-NFT: Analyzing Far-Right Extremism on Non-Fungible Tokens across different blockchains

To better understand the connection between NFTs and (far-right) extremist content, we collected 7.5k NFT and their metadata from 11 blockchains. Categorizing the NFT by their title, description, details and visual assessment of the downloaded images/GIFs/videos, we conclude that far-right extremist content is spread via NFTs on different blockchains. Looking at the metadata and images of pre-selected 4.5k NFT from a keyword search, only a small share of NFTs is clearly extremist (2%). Much more content with relevant keywords in NFT metadata could be used for extremist purposes but is not extremist per se (approx. 15 %).

We learned that more specific keywords, produce more relevant results, that extremist slang/code is propagated into NFT descriptions and yields more extremist results when searched for. But: Extremist code only produces clearer results as long as the keywords remain distinguishable and not context-dependent. Context-sensitive, extremist 'codes', such as number combinations, cannot be detected with a keyword-based search method. This produces an unknown share of undetected extremist NFTs. The classification process was done manually which is a time-consuming process that does not scale well with more data. Automatization or even AI-based approaches to support the manual work are challenging since the categorization as extremist remains contextual and usually requries a description-image-context combination.

Overall, the analysis remains a spot-check since it is not feasible to collect all NFTs across multiple chains. Just like collectable NFTs remain unseen if relevant keywords are unknown.