@inproceedings{240766e963a04d70bded7000e4270863,
title = "Agora: Introducing the Internet's Opinion to Traditional Stock Analysis and Prediction",
abstract = "This project aims to incorporate the aspect of sentiment analysis into traditional stock analysis to enhance rating predictions by applying a reliance on the opinion of various stocks from the Internet. Headlines from seven major news publications and conversations from Yahoo Finance's 'Conversations' feature were parsed through the Valence Aware Dictionary for Sentiment Reasoning (VADER) natural language processing package to determine numerical polarities which represented positivity or negativity for a given stock ticker. These generated polarities were paired with stock metrics typically observed by stock analysts as the feature set for a Logistic Regression machine learning model. The model was trained on roughly 1500 major stocks to determine a binary classification between a 'Buy' or 'Not Buy' rating and the results of the model were inserted into the back end of the Agora Web UI which emulates search engine behavior specifically for stocks found in NYSE and NASDAQ. The model reported an accuracy of 82.5% and for most major stocks, the model's prediction correlated with stock analysts' ratings. Given the volatility of the stock market and the propensity for hive-mind behavior in online forums, the performance of the Logistic Regression model would benefit from incorporating historical stock data and more sources of opinion to balance subjectivity in the model.",
keywords = "Logistic Regression, Sentiment Analysis, Stock Market, VADER",
author = "Jayanth Rao and Venkat Ramaraju and James Smith and Ajay Bansal",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 16th IEEE International Conference on Semantic Computing, ICSC 2022 ; Conference date: 26-01-2022 Through 28-01-2022",
year = "2022",
doi = "10.1109/ICSC52841.2022.00030",
language = "English (US)",
series = "Proceedings - 16th IEEE International Conference on Semantic Computing, ICSC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "147--150",
booktitle = "Proceedings - 16th IEEE International Conference on Semantic Computing, ICSC 2022",
}