Textrics- Find text-related solution | Sentiment | Emotion | Intent | Text-Tagging Analysis

  In this online world where we all are working 24*7 hours on the Internet, Analysing everything is now part of work. Despite having SSL on the website we need to verify everything before and after publishing our website.   If you have a blog site or online shopping store you need to know the content's impact on customers. Reviewing customers' thoughts is the only option to exposure of your own sites.   Natural Language Processing or NLP is a mixing technique of computer science, machine learning, which is the reason between the interactions of computers and humans. Created by humans, NLP sentiment analysis gives us a detailed analysis of any speech or text using machine learning. Natural Language processing analyses your spoken or written words via data processing and algorithm development. An online sentiment tool is a perfect tool to describe and analyze sentiments. With the help of advanced technology like Machine learning, natural language processing, text mining and...

  After 2019 companies are pushing their agenda to the online community and brand value. Brand value is the most important thing for companies nowadays. Brand value depends on customers reviews and how customers find its efficiency and value. Nowadays the epic increase of online community, review sites, customer comments after purchasing everything is now part of brand value. But it’s not possible for the website owner itself to check and find the intensity for each and every review of the product. That’s how the idea of ONLINE SENTIMENT ANALYSIS came Online sent i ment analysis or Emotion AI or Opinion Mining is the combination of natural language processing, text mining, and computational linguistics, and machine learning such as advanced technologies to extract emotions and sentiments information from any content. With the increased amount of Ecommerce websites, reviews, and commenting sites we can see a huge increase in NLP sentiment analysis software. Why  NLP sentiment a...