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Mar 6, 2024·Non-Fungible Tokens
2 cites
The Fetishizing Language behind the NFT Craze

Carlos Yebra López

This chapter explores the speculative nature of non-fungible tokens (NFTs) from the complementary perspectives of critical linguistics, cultural studies, and propaganda studies. I argue that the mainstream normalization of an idea, during the peak of the NFT rush (2021), that purely virtual objects could be worth millions of dollars was both reflected in and aided by the fetishizing and propagandistic conceptualization of NFTs as virtual assets, and that this conceptualization is best understood and transcended from the lenses of a semiotic and semantic critique. First, I examine the fetishization of NFTs as the signifier at the expense of NFT as a signified, resulting in self-referentiality. Second, I examine the detachment between signifier and signified as propagandistic with a focus on its catalyzation in a mass campaign of social media with a speculative economic agenda. Third, I argue for the need to rebridge the signified and signifier in the post-bubble phase of NFTs, disentangling the metaphorical and literal meanings of NFTs as digital assets.

Gender Studies in Language
Original source
Jul 19, 2018·Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)
0 cites
Using ethereum transactions to deanonymize senders

Siddharth Murali

The historic rise of blockchain-based cryptocurrencies to over $327 billion in market capitalization has sparked significant research efforts studying their reliability, performance, and security. Bitcoin, the highest valued cryptocurrency, has received the most thorough scrutiny, with many studies analyzing its peer properties and network health. In contrast, the network layer for Ethereum, the second-largest cryptocurrency, has gone mostly ignored, even though it employs different algorithms for transaction propagation. \n\nIn this thesis, we perform timing analysis on transactions propagated through Ethereum networks to identify the origin nodes. We build a tool called TxSniper to verify our approach on Ethereum's main network. We find that we can identify the origin with a 70% probability; this method is not always effective due to presence of nodes running clients that use different implementations of transaction propagation.

Open access
Historical Linguistics and Language Studies
Gender Studies in Language
Lexicography and Language Studies
Original source