Initial Coin Offerings Success Prediction Using Social Media and Large Language Models

Initial Coin Offering (ICO) is a fundraising method utilized by blockchain startups to raise capital by issuing and selling digital tokens to investors. ICOs have become widely popular for cryptocurrency fundraising, often generating millions of dollars, and surpassing traditional crowdfunding methods like Initial Public Offerings. However, ICO is a risky way of investing and raising capital due to the lack of regulations and standardisation. In this research, we delve into the impact of social media and sentiment analysis on the success of ICOs, employing various machine learning models and Large Language Models. Our analysis is based on data from over 1,000 ICOs gathered from diverse ICO information platforms, coupled with a corpus of 910,478 tweets associated with these ICOs. We extend our investigation to include other social media platforms such as BitcoinTalk, Telegram, Facebook, and Medium. Our analysis revealed that valuable insights regarding the success of ICOs can be derived by examining text sentiment and investigating metadata across these diverse social media channels.

Authors

Publication Details

Journal
Journal of Advances in Information Technology
Published
2025-01-01
DOI
https://doi.org/10.12720/jait.16.1.12-20
Citations
3
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
9.74
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Initial Coin Offerings Success Prediction Using Social Media and Large Language Models

Khouloud Safi Eljil, Farid Naït‐Abdesselam, Essia Hamouda
3 citations
Journal of Advances in Information Technology
Blockchain Technology Applications and Security
9.74
article

Initial Coin Offerings Success Prediction Using Social Media and Large Language Models

Khouloud Safi Eljil, Farid Naït‐Abdesselam, Essia Hamouda
article en
3 citations

Abstract

Initial Coin Offering (ICO) is a fundraising method utilized by blockchain startups to raise capital by issuing and selling digital tokens to investors. ICOs have become widely popular for cryptocurrency fundraising, often generating millions of dollars, and surpassing traditional crowdfunding methods like Initial Public Offerings. However, ICO is a risky way of investing and raising capital due to the lack of regulations and standardisation. In this research, we delve into the impact of social media and sentiment analysis on the success of ICOs, employing various machine learning models and Large Language Models. Our analysis is based on data from over 1,000 ICOs gathered from diverse ICO information platforms, coupled with a corpus of 910,478 tweets associated with these ICOs. We extend our investigation to include other social media platforms such as BitcoinTalk, Telegram, Facebook, and Medium. Our analysis revealed that valuable insights regarding the success of ICOs can be derived by examining text sentiment and investigating metadata across these diverse social media channels.

Journal of Advances in Information TechnologyVol. 16(1)
Openalex Percentile: Top 3%
Blockchain Technology Applications and Security
9.74
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.