Trust Dynamics and Bot-Driven Responses: An Approach to Rug Pulls in Solana Meme Coin Markets

This paper examines the dynamics of trust and bot-driven responses within the meme coin ecosystem on the Solana blockchain, with a particular emphasis on the interplay between social media-induced sentiment and on-chain transaction behaviors.Meme coins, which originate from internet culture and are heavily influenced by community sentiment, represent a volatile and distinct category of cryptocurrencies.Employing sentiment propagation networks, on-chain transaction data, and sentiment-transaction integrated models, we quantitatively analyze the relationship between emotional fluctuations and market behaviors.By contrasting Rug Pull scams with sustainable projects, we identify critical differences in the role of sentiment across different phases of project development.Our findings reveal three distinct sentiment-driven user trading behaviors: sentiment followers, makers, and stabilizers.The results indicate that, while sentiment is a primary driver of early-stage trading within Rug Pull projects, its influence diminishes as community distrust intensifies, resulting in more opportunistic and reactive trading patterns.This study contributes to the understanding of the co-evolution of memes, sentiment, and market dynamics, offering new insights into the complexities of decentralized finance ecosystems, with a specific focus on Solana-based meme coin markets.

Authors

Institutions

Publication Details

Published
2025-05-19
DOI
https://doi.org/10.1145/3717867.3717922
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trust Dynamics and Bot-Driven Responses: An Approach to Rug Pulls in Solana Meme Coin Markets

Nanjun Yao, Wei Cai, Yueyao Li, Yuhui Huo
Opinion Dynamics and Social Influence
article

Trust Dynamics and Bot-Driven Responses: An Approach to Rug Pulls in Solana Meme Coin Markets

Nanjun Yao, Wei Cai, Yueyao Li, Yuhui Huo
article en

Abstract

This paper examines the dynamics of trust and bot-driven responses within the meme coin ecosystem on the Solana blockchain, with a particular emphasis on the interplay between social media-induced sentiment and on-chain transaction behaviors.Meme coins, which originate from internet culture and are heavily influenced by community sentiment, represent a volatile and distinct category of cryptocurrencies.Employing sentiment propagation networks, on-chain transaction data, and sentiment-transaction integrated models, we quantitatively analyze the relationship between emotional fluctuations and market behaviors.By contrasting Rug Pull scams with sustainable projects, we identify critical differences in the role of sentiment across different phases of project development.Our findings reveal three distinct sentiment-driven user trading behaviors: sentiment followers, makers, and stabilizers.The results indicate that, while sentiment is a primary driver of early-stage trading within Rug Pull projects, its influence diminishes as community distrust intensifies, resulting in more opportunistic and reactive trading patterns.This study contributes to the understanding of the co-evolution of memes, sentiment, and market dynamics, offering new insights into the complexities of decentralized finance ecosystems, with a specific focus on Solana-based meme coin markets.

Chinese University of Hong Kong, Shenzhen (CN), University of Washington Tacoma (US)
Ministry of Industry and Information Technology of the People's Republic of China
Openalex Percentile: Top 91%
Opinion Dynamics and Social Influence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.