Hi! Let’s know more about Sentiment Analysis.

First of all, what’s sentiment analysis task?

Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.

What’s multi-language?

If you are wondering if it can perform sentiment analysis for many languages, it’s right! This API are built with state-of-the-art NLP model able to understand patterns of text in any language. Looking more deeper, we used the model Facebook BART MNLI and fine-tuned to sentiment analysis task.

What’s Aspect-based?

It refers to determining the opinions or sentiments expressed on different features or aspects of entities, e.g., of a cell phone, a digital camera, or a bank.[35] A feature or aspect is an attribute or component of an entity, e.g., the screen of a cell phone, the service for a restaurant, or the picture quality of a camera. The advantage of feature-based sentiment analysis is the possibility to capture nuances about objects of interest. Different features can generate different sentiment responses, for example a hotel can have a convenient location, but mediocre food.[36] This problem involves several sub-problems, e.g., identifying relevant entities, extracting their features/aspects, and determining whether an opinion expressed on each feature/aspect is positive, negative or neutral.[37] The automatic identification of features can be performed with syntactic methods, with topic modeling,[38][39] or with deep learning.[40][41] More detailed discussions about this level of sentiment analysis can be found in Liu’s work.[23]

Parameters

It receive two possible parameters, the text, and aspect. The text is simple, is just the document or text that you want process, the Aspect is about elements in the text that the model would consider to analyze the sentiment.

More details of the model: https://metatext.io/models/facebook-bart-large-mnli