Mitigation of Poetry Text into Emotional States Based on Twitter Real-time Dataset using Convolution Neural Network

Abstract

There are a lot of obstacles to progress in continuing to use social media poetry resources for evaluating consumer groups, but don't give up. A central role in human behaviour is played by feelings, there are also opportunities to observe emotions by text analysis in messages from social media for helping to identify psychiatric problems or observing the general public sentiment in a group. classification methods that relied on a lexicon and a "pack of vocabulary" used in previous studies The current study carried out using deep learning methods on the impact of hashtags found in Twitter has, although it does not allow for other potential hashtags that may not have existed during the time span the analysis was done. The algorithm aims to enhance the detection of emotions on real-time streaming financial data that's fetched from Twitter. the overarching goal is to correctly identifying all of this is to allow for proper understanding of the different emotions that a specific tweet conveys.