{"repo":"hamidm21/Revisit_FSA","free":true,"listed":false,"github":"https://github.com/hamidm21/Revisit_FSA","clone":"git clone https://github.com/hamidm21/Revisit_FSA.git","description":"Market-Derived Financial Sentiment Analysis: Context-Aware Language Models for Crypto Forecasting","language":"Jupyter Notebook","stars":19,"topics":["bitcoin","finbert","fsa","sentiment","sentiment-analysis","tbl"],"license":null,"category":"blockchain-web3","readme_excerpt":"Revisiting Financial Sentiment Analysis: A Language Model Approach corresponding code to the paper: https://arxiv.org/abs/2502.14897 Easy access - Neptune AI results for language model experiments can be found here including tables, confusion matrixes and more. - the main notebook on Kaggle called tweet-classification can be found here - the final implementation and optimization of Triple Barrier Labeling can be found in the notebook next day prediction - backtesting experiments and results can be found here How to run Experiments use poetry to install the packages with . for more information go to poetry docs then run with Project Folders and structure Here are the folders and what they contain: - raw: unprocessed data - dataset: processed data - notebook: notebooks - src: contains the source code for experiments Overall Architecture Summary of the Backtesting results","default_branch":null,"files":null,"tree":[],"storefront":"/r/hamidm21","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/hamidm21/Revisit_FSA/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}