Discursive use of stability in New York Times coverage of China: a sentiment analysis approach Humanities and Social Sciences Communications
Sentiment and emotion in financial journalism: a corpus-based, cross-linguistic analysis of the effects of COVID Humanities and Social Sciences Communications In the end, the GRU model converged to the solution faster with no large iterations to arrive at those optimal values. In summary, the GRU model for the Amharic sentiment dataset achieved 88.99%, 90.61%, 89.67% accuracy, precision, and recall, respectively. From Tables 4 and 5, it is observed that the proposed Bi-LSTM model for identifying sentiments and offensive language, performs better for Tamil-English dataset…