Emotion detection in conversations is a necessary step for a number of applications, including opinion mining over chat history, social media threads, debates, argumentation mining, understanding consumer feedback in live conversations, etc.
Emotion recognition in conversations is crucial for the development of empathetic machines.
#3 best model for Emotion Recognition in Conversation on IEMOCAP
We introduce a hybrid technique which combines machine learning and rule based model.
We introduce a Hindi-English (Hi-En) code-mixed dataset for sentiment analysis and perform empirical analysis comparing the suitability and performance of various state-of-the-art SA methods in social media.
Along with the advance of opinion mining techniques, public mood has been found to be a key element for stock market prediction.
Reproducing experiments is an important instrument to validate previous work and build upon existing approaches.
These results, as well as further experiments on domain adaptation for aspect extraction, suggest that differences between speech and written text, which have been discussed extensively in the literature, also extend to the domain of product reviews, where they are relevant for fine-grained opinion mining.