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      "body": "<h2>Introduction</h2>\n\n\nThe ubiquitous influence of Artificial Intelligence (AI) in customer service has helped enterprises include real-time-narrative mapping in chatbots. With this innovation, chatbots are capable of operating based on intent recognition and understanding human emotions; also known as Sentiment Analysis.\nSentiment Analysis is a natural language processing technique used to regulate whether data is neutral, positive, or negative. It is the process of determining whether a text conveys a good or bad statement about a topic or a product. Many companies use sentiment analysis as they don’t have to spend endless hours tagging customer data such as reviews, social media comments, support tickets, and survey responses. 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That is for example- very positive=5 stars and very negative= 1 star.\n\n<b>Emotion Detection</b>- This type of sentiment analysis detects various emotions such as happiness, anger, sadness, frustration, and so on. Most emotion detection systems use lexicons or complex ML algorithms.\n\n<b>Aspect-based sentiment</b>- When you’re looking through some product reviews, you will want to know which specific aspects or features are customers mentioning in a positive, neutral, or negative kind of way. That’s where Aspect-based sentiment falls in. \n\n<b>Multilingual Sentiment Analysis</b>- This is a difficult type of sentiment analysis that includes understanding and preprocessing of different languages. \n\nSentiment Analysis uses NLP(Natural Language Processing) and other algorithms like \n<i>Rules-based systems</i>- which is basically using a set of manually crafted rules.\n<i>Automatic systems</i>- relies on ML techniques to learn from data.\n<i>Hybrid systems</i>- this type of system combines both rule-based and automatic approaches.\n          \n<h2>How Sentiment Analysis Can improve Customer Service:</h2>\n\nUsing sentiment analysis you can examine the information, to recognize the emotions, attitudes, and tones of customers throughout all social media platforms, including emails, posts, and text conversations. You can then make use of this information, get more insights on what you need to provide or take care of your business/company to make it more beneficial and customer-friendly. \n\nThere are many benefits to utilizing sentiment analysis in customer service, they include-\n\n<b>Sentiment Categorization</b> - Sentiment analysis helps you to work with more specific/precise data. Hence, you can use this data to understand customer feedback. Further, you can categorize the sentiment, which allows you to know how customers really feel about your employees, physical and digital stores, websites, products, and services.\n\n<b>Problem Identification</b> - Unhappy customers mostly tend to let out their anger on “social media”, if they’re not satisfied with any services/products your company has provided. So with the help of sentiment analysis, you can keep track of your brand perception and avoid the potential setback. \n\n<b>Competitor Analysis</b> - Sentiment analysis also helps you track other competitors and can assist you in exploring how they are perceived in comparison to you. You can also make use of sentiment analysis to understand the trending topics on social media. In such a way, you can realize and get to know what your competitors are up to and which people they are targeting. This can be pivotal in predicting market trends and can help enterprises in providing a customer-centric service. \n\n<b>Clearer Understanding of Customer Feedback</b> - In order to get to know how people feel about your products or services, you can take the help of sentiment analysis. It assists you in improving your schemes and helps in reducing drawbacks by identifying them. 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      "body": "<h2>Introduction</h2>\n\n\nThe ubiquitous influence of Artificial Intelligence (AI) in customer service has helped enterprises include real-time-narrative mapping in chatbots. With this innovation, chatbots are capable of operating based on intent recognition and understanding human emotions; also known as Sentiment Analysis.\nSentiment Analysis is a natural language processing technique used to regulate whether data is neutral, positive, or negative. It is the process of determining whether a text conveys a good or bad statement about a topic or a product. Many companies use sentiment analysis as they don’t have to spend endless hours tagging customer data such as reviews, social media comments, support tickets, and survey responses. 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      "body": "Hello welcome to Steemit world! \n I'm @steem.history, who is steem witness. \n This is a recommended post for you.[Newcomers Guide](https://steemitdev.com/guide/@steemitblog/steemit-a-guide-for-newcomers) and [The Complete Steemit Etiquette Guide (Revision 2.0)](https://steemit.com/steem/@steem.history/the-complete-steemit-etiquette-guide-revision-20-homage-1598425779) and, recommended community [Newcomers Community](https://steemit.com/trending/hive-172186) \n I wish you luck to your steemit activities.<center> \n \n \n https://cdn.steemitimages.com/DQmXHwdcNs5VPcBft1iSosPdHLpBNBfjuG84g3ffWhMw5JQ/image.png \n <sub>(The bots avatar has been created using https://robohash.org/)</sub> \n @steem.history \n \n ### My witness activity \n - [My aspiration for STEEM witness](https://steemit.com/hive-185836/@steem.history/my-aspiration-for-steem-witness-1601280729) \n - Provides information on Steem.  \n [Reference](https://steemit.com/trending/hive-130095) \n - Supporting the Steem project. \n [SPUD4STEEM project](https://steemit.com/trending/spud4steem) \n - Supporting the community. \n [Newcomers Community](https://steemit.com/trending/hive-172186),[Steem Sri Lanka](https://steemit.com/trending/hive-133716) ,[WORLD OF XPILAR](https://steemit.com/trending/hive-185836), [GLOBAL STEEM](https://steemit.com/trending/hive-145160), [Scouts](https://steemit.com/trending/hive-181136), [Latino Community](https://steemit.com/trending/hive-188619) \n \n ### My featured posts \n - [The Complete Steemit Etiquette Guide (Revision 2.0) -Homage](https://steemit.com/steem/@steem.history/the-complete-steemit-etiquette-guide-revision-20-homage-1598425779) \n \n [![image.png](https://cdn.steemitimages.com/DQmd7of2TpLGqvckkrReWahnkxMWH6eMg5upXesfsujDCnW/image.png)](https://steemlogin.com/sign/account-witness-vote?witness=steem.history&amp;approve=1) \n <sub>please click it!</sub> \n \n ![image.png](https://cdn.steemitimages.com/DQmWDnFh7Kcgj2gdPc5RgG9Cezc4Bapq8sQQJvrkxR8rx5z/image.png) \n <sub>(Go to https://steemit.com/~witnesses and type fbslo at the bottom of the page)</sub> \n \n </center>",
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      "body": "<h2>Introduction</h2>\n\n\nThe ubiquitous influence of Artificial Intelligence (AI) in customer service has helped enterprises include real-time-narrative mapping in chatbots. With this innovation, chatbots are capable of operating based on intent recognition and understanding human emotions; also known as Sentiment Analysis.\nSentiment Analysis is a natural language processing technique used to regulate whether data is neutral, positive, or negative. It is the process of determining whether a text conveys a good or bad statement about a topic or a product. Many companies use sentiment analysis as they don’t have to spend endless hours tagging customer data such as reviews, social media comments, support tickets, and survey responses. 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You can then make use of this information, get more insights on what you need to provide or take care of your business/company to make it more beneficial and customer-friendly. \n\nThere are many benefits to utilizing sentiment analysis in customer service, they include-\n\n<b>Sentiment Categorization</b> - Sentiment analysis helps you to work with more specific/precise data. Hence, you can use this data to understand customer feedback. Further, you can categorize the sentiment, which allows you to know how customers really feel about your employees, physical and digital stores, websites, products, and services.\n\n<b>Problem Identification</b> - Unhappy customers mostly tend to let out their anger on “social media”, if they’re not satisfied with any services/products your company has provided. So with the help of sentiment analysis, you can keep track of your brand perception and avoid the potential setback. \n\n<b>Competitor Analysis</b> - Sentiment analysis also helps you track other competitors and can assist you in exploring how they are perceived in comparison to you. You can also make use of sentiment analysis to understand the trending topics on social media. In such a way, you can realize and get to know what your competitors are up to and which people they are targeting. This can be pivotal in predicting market trends and can help enterprises in providing a customer-centric service. \n\n<b>Clearer Understanding of Customer Feedback</b> - In order to get to know how people feel about your products or services, you can take the help of sentiment analysis. It assists you in improving your schemes and helps in reducing drawbacks by identifying them. You can track the customer feedback and understand the actions needed to be taken to prevent it in the future and try to deliver a positive customer experience. \n\n<b>Better Call Routing</b> - Whatever decisions your conversational Interactive Voice Response (IVR) makes, sentiment analysis plays an important role in it. This helps to resolve issues more quickly and allows the staff to learn how to deal with tough, and challenging situations. \n\n<b>Legislative Compliance</b> - Only relying on texts or spoken words isn’t really or always satisfying for compliance purposes. Sentiment analysis lays out a deeper understanding and meaning, hence assisting you to understand the truthfulness of an interaction. This helps to maintain your company’s reputation. \n\n<h2>Conclusion</h2>\n\nHence we’ve learned that sentiment analysis technology can be very beneficial for many businesses and companies as it delivers excellent customer service, along with other factors. There are numerous <a href=“https://thinkpalm.com/services/mobile-app-development-services/”>mobile app development services</a> companies that keep up with the latest market trends and understand what all chatbot-related products or services will be beneficial for the customers. In order for a company or a business to survive in the modern world, sentiment analysis plays a critical role. It gives you the potential to get to know how people feel about your brand and then you can use that insight to upgrade your customer service. It helps to transform your business and eliminate problems on a much better scale. The tech world is evolving much faster than ever before and the new era of enhanced customer service has begun.",
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