The phrase "accuracy of sentiment" is correct and usable in written English.
It can be used when discussing the precision or correctness of expressed feelings or opinions, often in contexts like data analysis, psychology, or social media.
Example: "The accuracy of sentiment analysis tools is crucial for understanding public opinion on social media platforms."
Alternatives: "precision of sentiment" or "correctness of sentiment".
We tried to see if Deep Learning models could improve the accuracy of sentiment analysis of StockTwits messages.
The machine learning techniques have improved accuracy of sentiment analysis and expedite automatic evaluation of data these days.
Long Jiang, Mo Yu, and Ming Zhou improved the accuracy of sentiment classification by merging characteristics and adding relevant text [14].
As our first step, we apply the doc2vec model to the StockTwits dataset to see if it can increase the accuracy of sentiment prediction for stock market writers.
Our goal is to examine whether these feature selection methods can reduce the feature sizes and improve the classification accuracy of sentiment analysis with respect to different document domains, languages, and classifiers.
In our paper, we mainly focus to see how Deep Learning can assist with sentiment analysis in StockTwits data and which Deep Learning algorithm can be adapted to improve the accuracy of sentiment analysis in StockTwits in compare to data mining models.
RNNs were adopted to see if they can help improve the accuracy of StockTwits sentiment analysis.
The most notable observation is that doubling the size of the training data, by adding negative sentiment training instances, did not improve results and, in fact, slightly lowered the accuracy of detecting positive sentiment spam reviews.
This study compares the product review sentiment classification accuracy of Algorithm TL with that of four other strategies: 1).
Given the growing assortment of sentiment-measuring instruments, it is imperative to understand which aspects of sentiment dictionaries contribute to both their classification accuracy and their ability to provide richer understanding of texts.
