KOREASCHOLAR

This study investigates social media posts on Twitter concerning cryptocurrency marketing. We applied unsupervised Latent Dirichlet Allocation (LDA) topic modeling and sentiment analysis techniques to 98,716 tweets to examine the Twitter content for subjects and sentiments related to cryptocurrency. We discovered that tweets about cryptocurrency fell into four categories, with “cryptocurrency trading,” “NFT airdrop,” “cryptocurrency affiliate program,” and “Dogecoin on social media” being the most popular. Most of the topics had positive sentiments. Theoretical and practical implications for developing cryptocurrency marketing communication strategies are discussed.

• Tae Hyun Baek(Sungkyunkwan University, Republic of Korea)
• Kwan Yi(Eastern Kentucky University, USA)