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In the volatile world of trading, success frequently depends on the ability to devise and implement effective methods. Understanding market sentiment has been increasingly important for stabilizing revenue and separating strategic trading from simply speculation since the advent of internet trading forums such as those on Reddit. This research offers a novel machine learning model that uses sentiment analysis to evaluate Reddit trading data, with the goal of providing traders with a better-informed decision-making base. This model tries to decipher the frequently complicated and trend-driven conversation within trading groups by merging techniques from machine learning, deep learning, and mathematical transformations–including VADER Analysis and Fourier Transforms, complemented by Long-Short Term Memory networks. The idea is to turn what often appears to be gambling into a more systematic approach to trading led by data-driven insights into market emotion.
Govinda et al. (Thu,) studied this question.