What is the translation of " SENTIMENT ANALYSIS " in Chinese?

• 情感分析
• 情绪分析
• 精神分析

Examples of using Sentiment analysis in English and their translations into Chinese

Why is sentiment analysis so important?
为何精神分析如此重要？?

One of the things we have worked on internally is sentiment analysis.
我们正在做的工作之一是内在情感分析。

Why sentiment analysis is so important?
为何精神分析如此重要？?

One of the most common uses for predictive analysis is sentiment analysis.
预测性分析最常见的用途之一是情绪分析。

Sentiment analysis, as described above, is a far from perfect science.
如上所示的情绪分析，是远远不如精确的科学。

In addition, even car companies are now evaluating the scope of sentiment analysis.
此外，甚至汽车公司现在正在评估情绪分析的范围。

In this Post you learned what Sentiment Analysis is and why Keras is one of the most used Deep Learning libraries.
在本文中，你了解到了什么是情感分析的内容，以及为什么Keras是最常用的深度学习库之一。

Further, even automotive companies are now evaluating the scope of sentiment analysis.
此外，即使汽车公司正在评估情绪分析的范围。

In my first blog, I looked at sentiment analysis, below I'm going to explore the common words people used across all voices.
在我的第一个博客里，我看了情绪分析，下面我将探讨人们在所有声音中使用的常用词。

Further, even automotive companies are now evaluating the scope of sentiment analysis.
此外，甚至汽车公司现在正在评估情绪分析的范围。

By using sentiment analysis, we hope to predict customers' opinions and attitudes towards the product based on the comments he wrote.
通过使用情绪分析，我们希望根据他撰写的评论，预测客户对产品的意见和态度。

Use cases include recommendation engines, fraud detection, predicting customer churn, sentiment analysis, and customer segmentation.
使用案例包括推荐引擎、欺诈检测、预测客户流失、情绪分析以及客户细分。

Sentiment analysis, however, is actually a complex and composite task that requires leveraging many different NLP techniques at the same time.
然而，情感分析是一个复杂、综合的任务，需要同时利用多种不同的NLP技术。

The explanation of a specific data use case in How to Perform Sentiment Analysis with Twitter Data was our ninth most read article of 2018.
关于如何使用Twitter数据进行情绪分析的特定数据用例的解释是我们2018年阅读量排名第九的文章。

Text analytics and sentiment analysis lets analysts review positive and negative results of marketing campaigns, or even identify online threats.
文本分析和情绪分析可让分析师检查营销活动的积极和负面结果，甚至识别在线威胁。

It also offers other features such as key phrase extraction, language detection, sentiment analysis, translation, and even identify entities in your text.
它还提供其他功能，如关键短语提取、语言检测、情感分析、翻译，甚至识别文本中的实体。

Sentiment analysis ranges from detecting emotions(e.g., anger, happiness, fear), to sarcasm and intent(e.g., complaints, feedback, opinions).
情感分析的范围从检测情感（例如愤怒，幸福，恐惧）到讽刺和意图（例如投诉，反馈，意见）。

Many of these have become familiar to mainstream computer users in the form of web search, question answering, sentiment analysis, and notably machine translation.
其中许多都变得广为人知，比如网络搜索，问答，情绪分析，尤其是机器翻译。

Market Sentiment Analysis is what determines whether the market is either a bull or a bear, depending on the current and future fundamental outlook.
市场情绪分析法用来确定，基于当前或未来的基本面前景，市场是处于牛市还是熊市。

The opportunity presented by“making sense” of unstructured information and the Natural Language Processing provided by Artificial Intelligence optimizes sentiment analysis.
理解”非结构化信息所呈现的机会以及人工智能提供的自然语言处理优化了情绪分析。

Sentiment analysis is a field within Natural Language Processing(NLP) concerned with identifying and classifying subjective opinions from text[1].
情感分析是自然语言处理（NLP）中的一个领域，涉及从文本中识别和分类主观意见[1]。

Some examples of the projects you could undertake with help from Ludwig include text or image classification, machine-based language translation and sentiment analysis.
用户可以在Ludwig的帮助下开展一些项目，其例子包括文本或图像分类、基于机器的语言翻译和情感分析。

In sentiment analysis techniques, machine learning techniques are used to annotate stock-related news stories or tweets and give an emotional score.
在情感分析技术中，机器学习技术被用来标注与股票相关资讯故事或推特，并给出一个情感分数。

It is a collection of related capabilities that include computer vision, sentiment analysis, language translation, natural language processing/ understanding and machine learning.
它是相关功能的集合，包括计算机视觉，情感分析，语言翻译，自然语言处理/理解和机器学习。

Sentiment analysis can be applied to many aspects of your business, from market research to customer service, or from product analytics to brand monitoring.
情感分析可应用于商业上无数的方面，从品牌监控到产品分析，从客户服务到市场研究。

It is increasingly used to deliver near-human level accuracy for image classification, voice recognition, natural language processing, sentiment analysis, recommendation engines, and more.
它越来越多地用于提供接近人类的水平精度图像分类，语音识别，自然语言处理，情感分析，推荐引擎等。

A popular classification example is sentiment analysis where class labels represent the emotional tone of the source text such as“positive” or“negative“.
流行的分类示例是情绪分析，其中类标签表示源文本的情绪基调，例如“积极”或“消极”。

Sentiment analysis(described below) is another secret weapon of machine learning in algorithmic trading, which is highly estimated by numerous hedge funds.
情绪分析（下文将会描述）是算法交易中机器学习的另一个秘密武器，这是众多对冲基金高度估量的。

While in industry, the term sentiment analysis is more commonly used, but in academia both sentiment analysis and opinion mining are frequently employed.
在工业中，情感分析这个术语更常用，在学术界，情感分析和意见挖掘都经常被使用。

As sentiment analysis continues to evolve, future virtual personal assistants and sentiment-sensitive wearables may understand our emotional state and preferences.
随着情绪分析的不断发展，未来虚拟个人助理和情感感应可穿戴设备可能会理解我们的情绪状态和偏好。