Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

5-2024

Abstract

With the advent of social network technology, the influence of collective opinions has significantly impacted business, marketing, and fundraising. Particularly in the blockchain space, Initial Coin Offerings (ICOs) gain substantial exposure across various online platforms. Yet, the intricate relationships among these elements remain largely unexplored. This study aims to investigate the relationships between social media sentiment, engagement metrics, and ICO success. We hypothesize a positive correlation between favorable sentiment in ICO-related tweets and overall project success. Additionally, we recognize social media engagement indicators (mentions, retweets, likes, follower counts) as critical factors affecting ICO performance. Employing machine learning techniques, we conduct sentiment analysis on tweets, discerning emotional nuances and categorizing expressions as positive or negative. Employing established classification methods, we further analyze engagement data to reveal its impact on ICO interest and awareness. Our research findings offer insights into the predictive potential of social media strategies for ICO success and underscore the importance of investor sentiment and engagement in the volatile cryptocurrency landscape. These insights provide actionable guidance for aspiring crypto founders in formulating effective business development strategies. The source codes and datasets of this paper are accessible at GitHub: https://github.com/inflaton/Success-Indicators-of-Initial-Coin-Offerings.

Keywords

Cryptocurrency, Initial Coin Offerings (ICOs), Machine Learning, Sentiment analysis, Social media

Discipline

Databases and Information Systems | Finance and Financial Management | Social Media

Research Areas

Data Science and Engineering

Areas of Excellence

Digital transformation

Publication

Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2024 Workshops, RAFDA and IWTA, Taipei, May 7-10: Proceedings

Volume

14658

First Page

57

Last Page

69

ISBN

9789819726509

Identifier

10.1007/978-981-97-2650-9_5

Publisher

Springer

City or Country

Cham

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1007/978-981-97-2650-9_5

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