Top 3 Best Sentiment Analysis APIs



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What is sentiment analysis or sentiment mining? It is part of NLP (Natural Language Processing) which is used to detect the emotions or feelings within specific text data, or from the transcription of audios or video files. A model will classify positive, neutral or negative sentiments. Currently there is deep learning towards expanding the range of feelings to include other reactions (enthusiastic, horrified, thrilled, etc.).

Sentiment analysis can work by taking written texts or transcription texts to generate output (positive, neutral or negative) on a 1 to -1 scale. This is also called sentiment polarity. Otherwise the mining can design sentiments by probability, defining percentages of positive, neutral or negative perceptions from the customers.

This is a useful approach to analyze interactions between customers and agents, assess conversations, and draw customers` feelings about products, services, agents, etc. This allows companies to pulse sentiments in participants in virtual meetings, adjust marketing strategies, improve products, train agents or issue communications.

How To Choose The Right API For Sentiment Analysis

The first step is to perform extensive deep learning research and set the company`s principles. The selection will depend on the budget, the language/s, the range of emotions to detect, the nature of your organization, and even the complexity of the expected analysis.

Zyla Labs Opinion Mining API guarantees high level of confidence for each sentiment or opinion, and it is a useful tool to sense feelings and reactions from your customers about your Company, products and/or services. By means of an audio or video transcription tool –both asynchronous and real-time- you can have a steady perception of feedback to introduce adjustments leading to improvement and eventual excellence. By means of Deep Learning research you get an output that serves its purpose to optimize production, services, timing and expense saving.

Amazon Comprehend for AWS Transcribe features customer conversation opinions and sentiments, content analysis in the media, subtitles and meeting notes, etc. Through sentiments tab, Amazon Comprehend can rate any text segment you select to check customers` perception, and provides probability rating for each ascribed sentiment. It also scores confidence for an assigned emotion.

IBM Watson Natural Language Understanding API will detect entities, types and categories, concepts, emotions and sentiments, relations, metadata and even semantic roles in transcription text with considerable accuracy. You can choose to analyze sentiments in detected entities or else in keywords. It assigns a score, and then the correct sentiment is given. You just enter a custom model ID and the standard sentiment model will be overridden. This API detects anger, disgust, fear, joy or sadness in a selected text segment.

Text analysis APIs for Word Associations, Sentiment Analysis, Emotion Analysis and Text Similarity are relevant tools for organizations, to gauge the public opinion so as to generate improvement in their products or services, alongside with adjustments in the structure, logistics and professional potential. With the evolution in neurosciences and the approach to emotional intelligence, Sentiment Mining is essential to get closer to the customer to know how they feel and perceive the company.

There are no limits to what Sentiment Mining APIs can do, as all texts from every source, as well as audios and videos, chats and media sites can be skimmed for the benefit of your organization. It is worth exploring, selecting and subscribing.

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