Sentiment Analysis of Artificial Stock Markets

This study will examine a dataset that contains 352 observations with 36 distinct variables. The dataset reflects people's thoughts and sentiments regarding a realistic fiction stock market game. The reason for analyzing this data is to identify any trends or patterns that might explain why specific persons or groups express specific sentiments toward the stock market. This study will analyze several characteristics that may correlate or provide a broad idea of why these specific groups may have favorable or unfavorable feelings toward the stock market. Questions categorize these characteristics. The participants are posed with questions pre-study and post-study in order to develop comparative results. The questions will probe each individual's knowledge of trading and their general intentions upon completing the stock market game. The majority of the study will center on the characteristic known as sentiment. Along with sentiment, machine learning, data visualizations, data mining, and behavioral analytics will analyze the dataset. Further analysis will provide more precise results. Due to the popularity surrounding sentiment, machine learning, data visualizations, data mining, and behavioral analytics. Overall, the study will analyze how people feel toward the stock market and whether or not there are correlations between those emotions and success or failure