Twitter sentiment analysis is the task of performing sentiment analysis on tweets from Twitter.
A novel social networks sentiment analysis model is proposed based on Twitter sentiment score (TSS) for real-time prediction of the future stock market price FTSE 100, as compared with conventional econometric models of investor sentiment based on closed-end fund discount (CEFD).
The posts or tweets from this data can be used for mining people's opinions.
Once we are happy with the quality of our input data, we proceed to choosing the optimal deep learning architecture for this task.
Sentiment analysis on large-scale social media data is important to bridge the gaps between social media contents and real world activities including political election prediction, individual and public emotional status monitoring and analysis, and so on.
Sentiment analysis is the process of identifying the opinion expressed in text.
A multilabel classification system Tw-StAR was developed to recognize the emotions embedded in Arabic, English and Spanish tweets.