Text Classification using Sentiment Analysis

   Customer sentiment analysis is the automated process of discovering emotions in online communications to find out how customers feel about your product, brand, or service. Sentiment analysis gives you a clear overview of customer satisfaction, agent by agent. This means you can keep an eye on the quality of service each team member is offering customers, as well as their more subtle ability to create happy customers. Here are some benefits of sentiment analysis telling us why it is important, • Happy customers are more likely to be receptive to upselling. With sentiment analysis,you can easily identify your happiest customers.  • If you have a chatbot on your site, it can benefit from sentiment analysis too. That’s because it can train your chatbot to recognise, and respond to, customer mood. • Using sentiment analysis, you can identify what messages and conversations act as emotive triggers that change customer mood. Perhaps the phrase “Please wait”, for example...

  Sentiment analysis  is the automated process of analyzing text to  determine the sentiment expressed (positive, negative or neutral). Some popular sentiment analysis applications include social media monitoring, brand monitoring, voice of customer, customer service and market research. 1)Social media monitoring Social media posts often present some of the most truthful points of view about products, services, and businesses because users offer their opinions unsolicited. They are simply compelled to tell the world how they feel.  But, with the help of  machine learning software , you can wade through all that data in minutes, to analyze individual emotions and overall public sentiment on every social platform. 2)Brand Monitoring Brand monitoring is one of the most popular applications of sentiment analysis in business. With the help of sentiment analysis tool you will be notified about negative brands immediately. And also you can track your...

  Sentiment analysis mainly focus on polarity, feelings and emotions,  urgency also on intentions. ·          Polarity (positive, negative, neutral) ·          Feelings and Emotions (angry, happy, sad etc.) ·          Urgency (urgent, not urgent) ·          Intentions (interested, not interested) Depending on how you want to interpret customer feedback and  queries, you can define and tailor your categories to meet your sentiment analysis needs. here are some of the popular types of sentiment analysis: 1)Fine-grained sentiment analysis Fine - grained sentiment analysis  of social media with emotion sensing. There   are polarity categories available such as : Very positive Positive Neutral Negative Very negative This is usually referred to as fine-graine...

  WHAT IS SENTIMENT ANALYSIS ? Sentiment Analysis is the most common text classification tool that analyses an incoming message and tells whether the underlying sentiment is positive, negative our neutral. It’s often used by businesses to detect sentiment in social data, gauge brand reputation, and understand customers. Since customers express their thoughts and feelings more openly than ever before, sentiment analysis is becoming an essential tool to monitor and understand that sentiment. Automatically analysing customer feedback, such as opinions in survey responses and social media conversations, allows brands to learn what makes customers happy or frustrated, so that they can tailor products and services to meet their customers’ needs. For example, using sentiment analysis to automatically analyse 4,000+ reviews about your product could help you discover if customers are happy about your pricing plans and customer service.         ...

  Natural language processing  ( NLP ) is a subfield of linguistics , computer science , and artificial intelligence  concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural data . NLP is field of AI that gives the machines the ability to read, understand and derive meaning from human languages. Real world applications of NLP are name entity recognition, machine translation, machine question answering etc. Before that we need to understand what is text classification. Text classification is process of categorizing text into organized  groups. Text classification is also called as text categorization and text tagging. Different websites, emails, chat conversations, social median contain unstructured text so it is very difficult for computer to understand such text and it is hard to extract a value from it unless and until it is organized in certain way. It is not p...