What is Sentiment Analysis?
Sentiment analysis, also known as opinion mining, is a natural language processing technique (NLP) used to determine the sentiment or emotional tone expressed in a piece of text, such as a tweet, customer review, or news article.
Sentiment Analysis API typically accepts text as input and provides an analysis of the sentiment associated with that text as output. The API utilizes machine learning algorithms and linguistic analysis to classify the sentiment as positive, negative, or neutral. Some advanced APIs can also provide sentiment intensity scores or fine-grained sentiment analysis, capturing subtle nuances in the expressed emotions.
Sentiment Analysis APIs uses cases
You can use Sentiment Analysis in numerous fields, here are some examples of common use cases:
- Customer Experience Management: analyze customer feedback from various sources, such as surveys, reviews, and social media comments.
- Market Research: assist in market research by analyzing consumer opinions and sentiments expressed in surveys, online forums, and product reviews.
- Finance and Investment: analyze news articles, social media posts, and financial reports to assess market sentiment and predict stock market trends.
- Healthcare: analyze patient reviews, healthcare surveys, and social media posts related to healthcare experiences.
- Brand Management: help businesses monitor and manage their brand reputation by analyzing sentiment associated with brand mentions, online reviews, and customer feedback.
- Political Analysis: analyze public opinions expressed on social media or in news articles related to political figures, policies, or events.
These are just a few examples of Sentiment Analysis APIs’s use cases. This technology can be applied in different fields to extract valuable insights from textual data and drive informed decision-making.
Best Sentiment Analysis APIs on the market
While comparing Sentiment Analysis APIs, it is crucial to consider different aspects, among others, cost security and privacy. Sentiment Analysis experts at Eden AI tested, compared, and used many Sentiment Analysis APIs of the market. Here are some actors that perform well (in alphabetical order):
- AWS
- Connexun
- Emvista
- Google Cloud
- IBM
- Lettria
- Microsoft Azure
- NLP Cloud
- OneAI
- OpenAI
- Tenstorrent
- Twinword
1. AWS - Available on Eden AI
AWS offers an advanced sentiment analysis API through Amazon Comprehend. This powerful tool enables users to determine the sentiment of text documents in various languages with accurate sentiment classification and support for positive, negative, mixed, and neutral sentiments. The API provides operations like DetectSentiment, BatchDetectSentiment, and StartSentimentDetectionJob, delivering sentiment scores to assess detection accuracy.
2. Connexun - Available on Eden AI
Leveraging state-of-the-art text vectorization techniques and machine learning classifiers, Connexun provides precise sentiment evaluation for text in multiple languages. What sets Connexun apart is its unique capability to analyze sentiment within the context of entities. By training their models on meticulously labeled datasets, Connexun ensures to deliver reliable and high-quality results.
3. Emvista - Available on Eden AI
Emvista provides a powerful sentiment analysis API that excels in both accuracy and explainability. Emvista offers a user-friendly web solution called Text Radioscope, which seamlessly connects to various sources of textual information such as Twitter, ZenDesk support tickets, and email inboxes. By visualizing sentiments along with keywords, concepts, opinions, and emotions in the form of curves, histograms, and word clouds, Text Radioscope enables users to quickly and easily extract valuable insights from their text data. This unique approach allows users to uncover knowledge that may not be immediately apparent, especially when cross-referencing large datasets.
4. Google Cloud - Available on Eden AI
With Google Cloud's Sentiment Analysis, users can examine text and accurately identify the dominant emotional opinion expressed, whether it's positive, negative, or neutral. Google Cloud's API stands out for its robustness and accuracy, allowing businesses to gain deep insights into the sentiment conveyed in their textual data. By leveraging Google's powerful infrastructure and cutting-edge algorithms, users can make informed decisions based on a clear understanding of the sentiment expressed in their text, leading to improved customer satisfaction, effective brand management, and enhanced decision-making processes.
5. IBM - Available on Eden AI
IBM offers a comprehensive sentiment analysis API through its Watson NLP platform. By offering a common framework for NLP, document understanding, translation, IBM Watson NLP simplifies the development and deployment process for sentiment analysis projects. This eliminates the need for multiple disjointed tools and ensures consistency throughout the analysis pipeline. Whether utilizing pre-trained models or fine-tuning a sentiment analysis model using the watson_nlp library, IBM Watson empowers companies to gain valuable insights from text data and effectively understand customer voice or market sentiment.
6. Lettria - Available on Eden AI
Lettria’s API stands out by utilizing psychology-based resources and Plutichik's wheel of emotions. By categorizing emotions into eight primary categories, including joy, sadness, fear, anger, disgust, attraction, surprise, and anticipation, enabling a comprehensive analysis of customer sentiments. This approach allows businesses to gain a deeper understanding of their customers' exact emotions towards their products or services, even when dealing with multiple emotions simultaneously. Additionally, Lettria's API can automatically rout relevant reviews to the appropriate departments for swift action, ensuring efficient customer support and issue resolution. Furthermore, by tracking trends and visualizing review data on specific aspects, businesses can uncover valuable insights and make informed decisions.
7. Microsoft Azure - Available on Eden AI
Microsoft Azure provides a powerful API through its Cognitive Service for Language. Azure's sentiment analysis and opinion mining features go beyond simple sentiment labels by mining text for clues about positive or negative sentiment and associating them with specific aspects of the text. Supporting a wide range of written languages, Azure provides sentiment labels and confidence scores at both sentence and document levels, allowing businesses to understand the overall sentiment as well as the sentiment of individual sentences. On the other hand, opinion mining provides granular information about opinions related to specific words or attributes in the text.
8. NLP Cloud
NLP Cloud offers a comprehensive API with the added capability of emotion analysis. Their API provides out-of-the-box sentiment and emotion analysis based on various powerful models such as GPT-J, GPT-NeoX, Dolphin, etc. These models exhibit excellent performance and impressive accuracy, delivering reliable results. NLP Cloud allows users to choose between using pre-trained models or training their own models, providing flexibility and customization options. With a focus on reliability, NLP Cloud ensures good response times and offers the ability to test sentiment and emotion analysis locally before deploying in production.
9. OneAI - Available on Eden AI
With advanced NLP algorithms, One AI offers exceptional accuracy in understanding and interpreting the nuances of human emotions expressed in text. The API goes beyond simple positive or negative classifications by highlighting detailed information, capturing the varying degrees of sentiment and emotional tones. Additionally, One AI's sentiment analysis API offers a user-friendly interface, seamless integration options, and robust scalability, making it an ideal choice for businesses and developers seeking a comprehensive and efficient sentiment analysis solution.
10. OpenAI - Available on Eden AI
Powered by OpenAI's state-of-the-art language models, the API offers several advantages. One of their key benefits is the ability to understand and interpret context, allowing for a deeper understanding of the analysis. OpenAI's solution also excels at handling complex and nuanced emotions, enabling more sophisticated results. Furthermore, the API offers a high level of flexibility and customization, allowing developers to fine-tune the sentiment analysis model to suit specific use cases.
11. Tenstorrent - Available on Eden AI
By harnessing their advanced AI computing solutions, Tenstorrent offers highly efficient and scalable sentiment analysis algorithms that deliver outstanding accuracy and performance. Their NLP solution excels at comprehending the nuanced aspects of human sentiment, capturing the intricate details and emotional nuances conveyed in text data. With its state-of-the-art technology, Tenstorrent's Sentiment Analysis empowers businesses and developers to extract valuable insights from vast amounts of text data swiftly and accurately.
12. Twinword
While it excels in quickly identifying negative comments from a large volume of user responses or reviews, Twinword's API offers additional benefits. This technology allows users to define their own criteria for what they consider positive or negative. This level of customization empowers businesses to align the sentiment analysis results with their specific needs and preferences. With Twinword's Sentiment Analysis API, businesses can effectively identify customer preferences, address concerns, and tailor their offerings to meet the needs and expectations of their target audience.
Performance variations of Sentiment Analysis APIs
For all companies who use Sentiment Analysis in their software: cost and performance are real concerns. The Sentiment Analysis market is quite dense and all those providers have their benefits and weaknesses.
Performances of Sentiment Analysis vary according to the specificity of data used by each AI engine for their model training. This means that some APIs may perform great for some languages but won’t necessarily for others.
Performance variations according to the languages
Sentiment Analysis APIs perform differently depending on the language of the text and some providers are specialized in specific languages. Different specificities exist
- Region specialties: some Sentiment Analysis APIs improve their machine learning algorithm to make them accurate for text in specific languages spoken in particular countries or regions. For example, some APIs perform well in English (US, UK, Canada, South Africa, Singapore, Hong Kong, Ghana, Ireland, Australia, India, etc.), while others are specialized in Asian languages (Korean, Japanese, Chinese, etc.).
- Rare language specialty: some Sentiment Analysis providers care about rare languages and dialects. You can find Sentiment Analysis APIs that allow you to process text in Gujarati, Marathi, Burmese, Pashto, Zulu, Swahili, etc.
Performance variations according to fields
Some Sentiment Analysis APIs trained their engine with specific data. Some APIs may excel at analyzing sentiment in general texts while others APIs can perform better on reviews or social media post.
Why choose Eden AI to manage your Sentiment Analysis APIs
Companies and developers from a wide range of industries (Social Media, Retail, Health, Finances, Law, etc.) use Eden AI’s unique API to easily integrate Sentiment Analysis tasks in their cloud-based applications, without having to build their own solutions.
Eden AI offers multiple AI APIs on its platform amongst several technologies: Text-to-Speech, Language Detection, Summarization, Data Anonymization, Speech Recognition, Face Detection, and so forth.
We want our users to have access to multiple Sentiment Analysis engines and manage them in one place so they can reach high performance, optimize cost and cover all their needs. There are many reasons for using multiple APIs :
- Fallback provider is the ABCs: You need to set up a provider API that is requested if and only if the main Sentiment Analysis API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
- Performance optimization: After the testing phase, you will be able to build a mapping of providers’ performance based on the criteria you have chosen (languages, fields, etc.). Each data that you need to process will then be sent to the best Sentiment Analysis API.
- Cost - Performance ratio optimization: You can choose the cheapest Sentiment Analysis provider that performs well for your data.
- Combine multiple AI APIs: This approach is required if you look for extremely high accuracy. The combination leads to higher costs but allows your AI service to be safe and accurate because Sentiment Analysis APIs will validate and invalidate each other for each piece of data.
How Eden AI can help you?
Eden AI has been made for multiple AI APIs use. Eden AI is the future of AI usage in companies. Eden AI allows you to call multiple AI APIs.
- Centralized and fully monitored billing on Eden AI for all Sentiment Analysis APIs.
- Unified API for all providers: simple and standard to use, quick switch between providers, access to the specific features of each provider.
- Standardized response format: the JSON output format is the same for all suppliers thanks to Eden AI's standardization work. The response elements are also standardized thanks to Eden AI's powerful matching algorithms.
- The best Artificial Intelligence APIs in the market are available: big cloud providers (Google, AWS, Microsoft, and more specialized engines)
- Data protection: Eden AI will not store or use any data. Possibility to filter to use only GDPR engines.
You can see Eden AI documentation here.
Next step in your project
The Eden AI team can help you with your Sentiment Analysis integration project. This can be done by :
- Organizing a product demo and a discussion to better understand your needs. You can book a time slot on this link: Contact
- By testing the public version of Eden AI for free: however, not all providers are available on this version. Some are only available on the Enterprise version.
- By benefiting from the support and advice of a team of experts to find the optimal combination of providers according to the specifics of your needs.
- Having the possibility to integrate on a third-party platform: we can quickly develop connectors
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