To understand the mindset of various people through online sources, sentiment analysis is one of the best option you can use. And social media content moderation is the right online platform where sentiment analysis process can be used to analyze the sentiments of the people and know their feelings and opinions.
People talking about particular things, discussing social issues and various other matters, they express their feelings towards a particular brand, product, services, company and organization. On social platforms, apart from written texts, people also sue emoji’s to express their feelings. So, there are different types of sentiments analysis are used to analyze the sentiments of the people.
Different Types of Sentiment Analysis
Basically, there are three types of sentiments – positive, negative and neutral along with more intense emotions like angry, happy and sad or interest or not interested etc. Further you can find here more refined sentiments used to analyze the sentiments of the people in different scenarios.
- Very positive
- Very negative
Actually, sentiments refer to attitudes, opinions, and emotions. Means they are subjective impressions as opposed to objective facts. Different types of sentiment analysis deep learning use different strategies and techniques to identify the sentiments contained in a particular text. So in more precise, there are two main types of sentiment analysis.
Subjectivity or Objectivity Identification:
Subjectivity/objectivity identification involves classification of a sentence or a fragment of text into one of two categories: subjective or objectivity. Though, it should be noted that there are challenges when it comes to conducting this type of analysis. The main challenge is that the meaning of the word or even a phrase is often contingent on its context.
Feature or Aspect-Based Identification
Feature or aspect identification allowing the determination of different opinions or sentiments (features) in relation to different aspects of an entity. Unlike subjectivity/objectivity identification, feature/aspect based identification allows for a much more nuanced overview of opinions and feelings that helps to get more in-depth feelings of the people around us.
Sentiment Analysis Dataset for Machine learning
Machine learning and AI models are now also developed to analyze the sentiments of the people. And to train such models, huge amount of training data sets are required. Cogito also provides the training data sets for sentiment analysis with best level of accuracy. Such data is also annotated for NLP and language based deep learning training and model development to analyze the sentiments of different people.
Cogito provides sentiment analysis services for wide ranging people from different background. It can analyze the sentiments of the people and understand their feelings and more in-depth state of mind that helps business organizations to understand their customers better. It can utilize the power of its experts who can easily read of the minds of people to provide them right product and services.