Targeted aspect-based emotion analysis to detect opportunities and precaution in financial Twitter messages

arXiv:2404.08665v1 Announce Type: cross
Abstract: Microblogging platforms, of which Twitter is a representative example, are valuable information sources for market screening and financial models. In them, users voluntarily provide relevant information, including educated knowledge on investments, reacting to the state of the stock markets in real-time and, often, influencing this state. We are interested in the user forecasts in financial, social media messages expressing opportunities and precautions about assets. We propose a novel Targeted Aspect-Based Emotion Analysis (TABEA) system that …

abstract analysis arxiv cs.cl cs.ir cs.lg cs.si emotion example financial information investments knowledge market markets messages opportunities platforms q-fin.tr real-time screening state stock stock markets them twitter type