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Customer service chatbot with sentiment analysis

MoonCampaign by Noah (9 years)

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Krish, a young innovator, has got the opportunity to exhibit "Customer service chatbot with sentiment analysis", his creation, to a live audience of 1500, including world-class entrepreneurs, leaders, and investors at the upcoming MoonBattle Conference 2024 in Milpitas. He will showcase "Customer service chatbot with sentiment analysis" in the Show and Tell Competition.    

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  • 🎁 27 days left

Your support will go a long way in encouraging Noah and taking their innovation Customer service chatbot with sentiment analysis to new heights.

Customer service chatbot with sentiment analysis

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Our Social Impact - We're transforming education globally with free robotics and math workshops in the US, UK, Canada, and Australia. Our workshops have helped 66,000 students alone in the US plus 14,000 students benefit from our four-week sessions.

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Learning Journey

  • Moonpreneur STEM Program Student

    Project Name: Customer service chatbot with sentiment analysis

  • Skills

    Arduino programming, sensor integration, conditional logic, product design, and more

  • Category

    Show n Tell

Impact of MoonCampaigns

MoonCampaigns highlight student's creativity, public speaking, presentation skills, and teamwork, with an impressive track record that speaks volumes. MoonCampaigns, through quarterly Show & Tell, highlight thousands of inspiring learning stories from Moonpreneur students worldwide.

5000+

Innovative MoonCampaigns

20,000+

Minutes of Visual Content

1M+

Unique Video Views

40,000+

Unique Feedbacks and appreciation to kids from community

80%

parents observed transformational changes in their ward's STEM knowledge and leadership skills

95%

Parents Reported Increased Confidence in their child

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STORY

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Congratulations to Krish for designing "Customer service chatbot with sentiment analysis" & being part of the upcoming MoonBattle Conference 2024 in Milpitas, Silicon Valley

  My project uses sentiment analysis to generate a response based on the sentiment of the user after answering a question/prompt given by the computer. It generates a polarity score based on the user’s response that determines the sentiment. The score ranges from -1 to +1 and is generated with the help of python’s Textblob library. My project makes customer service effortless, powered by sentiment analysis to detect the mood of the user, and then generate a response accordingly. My program chooses from a pool of questions such as "Have you shopped with us before? If yes, what was your previous experience?" and  "Were you able to find everything that you were looking for?", and then takes an answer from the user. Once the answer has been provided, a sentiment score ranging from -1 to +1 is generated (lower scores indicate sad and angry emotions and vice versa). After the score is generated, the program selects a response to output accordingly. To conclude, we can harness the power of sentiment analysis to greatly improve customer service.    

If you like Krish' project, support "Customer service chatbot with sentiment analysis" by sharing and liking it.

       
  • Develop a chatbot to automatically analyze user feedback and generate appropriate responses using natural language processing.
  • Provide a tool to streamline communication processes and improve customer satisfaction by efficiently addressing user concerns and inquiries.

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Customer service chatbot with sentiment analysis project

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