自然(考古学)
自然语言处理
计算机科学
心理学
沟通
人工智能
语音识别
认知心理学
生物
古生物学
作者
M. S. Antony Vigil,Amit Anand,Jasjit Singh,Sri Prakash Misra
标识
DOI:10.53555/jaz.v45i1.3692
摘要
Sentiment analysis, also known as opinion mining, is a Natural Language Processing (NLP) technique that holds a pivotal role in discerning textual data's sentiments, categorizing them as positive, negative, or neutral. Its significance is underscored by its widespread use in aiding businesses to gauge brand and product sentiment from customer feedback, enhancing customer service, and identifying areas for product and service improvement. Moreover, sentiment analysis offers the ability to track sentiments in real-time, helping companies retain existing customers and attract new ones cost-effectively. Emotion recognition in animals using Natural Language Processing (NLP) is a challenging and less explored area compared to human emotion recognition. While animals do communicate their emotions through various non-verbal cues, such as body language, vocalizations, and facial expressions, applying NLP techniques directly may not be straightforward since animals don't use language in the same way humans do. However, if there are textual data associated with animal behavior, such as ethological observations or written descriptions of their activities, NLP techniques can be adapted to gain insights into their emotional states.
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