Скачать или смотреть Machine Learning Detects Emotions From Videos. Natural Language Processing Part 2

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Sentiment Analysis is used to classify content as positive, negative, or neutral. It is also sometimes referred to as Sentiment Mining because it works to identify and extract, or mine, these sentiments in your source material.

The Sentiment Analysis feature can help you extract even more useful information from your audio and video files. Some ways our customers currently use Sentiment Analysis include:
1. To determine the sentiments of customer-agent conversations, say in a call center conversation. Determining customer sentiment based on agent interactions, topics, locations, and more. Identifying agent sentiments to facilitate better training and customer service.
2. To extract the sentiments in virtual meetings by speaker, topic, location, meeting time, and more. Using defined sentiments for analytics that inform product development, marketing, and customer service.
3. To define the sentiment of news stories in news coverage. Analyze anchor or caller sentiments by topic, political affiliation, time of day, and more.

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