In 2022, Sentiment Analysis can be a powerful tool for companies. In this article, we will give you the best ai technologies for your business.
Sentiment analysis, often known as opinion mining, is a natural language processing (NLP) technique for determining the emotional tone of a body of text. This is a common method for businesses to determine and categorize customer opinions about a product, service, or concept.
To get started with sentiment analysis, you had to analyze hundreds of data. You can now automate the process and provide your team with the insights they need to meet their objectives by using one of the many sentiment analysis tools available. Your media monitoring project should include sentiment analysis as a standard component.
Nowadays, many businesses use an application programming interface (API), which is one of the most powerful AI technologies. Because it is a piece of software that lets two applications communicate with each other, an API collects data from multiple sources in real-time.
However, with so many AI technologies available on the internet, deciding which one is suitable for you can be tough. As a consequence, we’ve determined that these tools are the most suitable option for you.
1-Klazify
Klazify allows you to classify any text in real-time by email, URL, and domain. This API categorizes all data in order to get the most useful data for your company. Furthermore, this API scans a website’s content and meta tags for the text and divides it into up to three groups using machine learning (ML) and natural language processing (NLP).
Klazify provides specific information about a business, such as revenue ranges for employees, logo APIs, location, tags, apps used, and industry type. The information is current and correct.
2-Lexalytics
Lexalytics has you covered whether you’re processing large amounts of text data, need security to run the system behind your firewall, or want to modify and configure your text analytics.
To begin, Lexalytics break phrases and sentences apart using text deconstruction and natural language processing to assess semantics, grammar, and other factors. Sentiment analysis, as well as classification, name entity recognition, intention detection, and other techniques, are used in the second step. Finally, structured data and conclusions are integrated into their data visualization suite or business intelligence systems, making historical and predictive analytics easy for the user.
3-Meaning Cloud
Meaning Cloud offers a diverse range of goods, including a sentiment analysis tool. The text is analyzed using their API, which identifies individual phrases and evaluates their interrelation.
Global sentiment, which is a general opinion expressed in a given mention, sentiment at attribute level, which provides a detailed analysis of sentiment in each sentence, identification of opinions and facts, and agreement and disagreement, which are messages for and against the analyzed content, are just a few of the features.
Also published on Medium.