Abstract:
Social Networking Sites (SNSs) are online platforms in which users present their lifestyles and opinions, share information and news, and communicate with other users. SNSs have been the preferred source of information for doing academic research on any subject. In this thesis, the interest areas of Twitter users who tweeted about cryptocurrencies were scrutinized by analyzing their tweets with a topic extraction algorithm. Little research has been conducted to identify the interest areas of cryptocurrency users in the current literature. As the data source, Twitter is chosen because Twitter provides current and historical data with easy access through Twitter Application Programming Interfaces (APIs). In order to reach Twitter users, a search query consisting of the keywords to be used was created. The keywords included “bitcoin, ethereum, ripple, btc, blockchain, fintech, and cryptocurrency”. Therefore, the data composed of tweets that were collected from Twitter users who tweeted about cryptocurrencies. These tweets were analyzed by using Latent Dirichlet Allocation (LDA), which is one of the well-known topic extraction algorithms. According to the result of LDA, Twitter users tweeted about cryptocurrency are found to be also interested in politics, economy, disruptive technologies, digital banking, social life, and data science.
