Improved Sentiment Urgency Emotion Detection for Business Intelligence
作者： Tariq Soussan , Marcello Trovati
DOI: 10.1007/978-3-030-57796-4_30
关键词:
摘要: The impact of social media on people’s lives has significantly grown over the last decade. Individuals use it to promote discussions and a way acquiring data. Industries market their goods facilities, advise inform clients about future offers, follow up direct market. It also offers vital information concerning general emotions sentiments directly connected welfare security. In this work, an improved model called Improved Sentiment Urgency Emotion Detection (ISUED) been created based previous work for opinion mining implemented with Multinomial Naive Bayes algorithm three classifiers which are sentiment analysis, urgency detection, emotion classification. will be trained improve its accuracy F1 score so that precision percentage correctly predicted texts is elevated. This applied same data set acquired from business Twitter account one largest chains supermarkets in United Kingdom able see what can detected how urgent they are.
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