In a world where to generate 2.5 quintillion bytes of data is being generated every day, Sentiment Analysis has become a key component to systematically extract, identify, and quantify the data Different social media like facebook, twitter LinkedIN are use sentiment analysis for there best user experiences. Nepali Sentiment Analysis is hardly found, which has immense possibilities, it tends to revolutionize the surveys and review collections in Nepal with its growing applicability to a wide variety of applications from customer service to marketing.
Nepali Sentiment Analysis generally consists of sample Nepali data collection, data processing, feature extraction, and classification. Not specific, we used generalize sentiment analysis approach. The extracted features should be able to classify the data reliably into a positive, negative, or neutral class.
For example:
मलाई यो मन परे न। [ Negative ]
आहा कती राम्रो घडी। [ Positive ]
Who used this Project.
This is not exactly a full and functional project with its won UI but it is just widgets or plugins or packages that can add to existing projects. It generates reports in the backend.
- Goverment Offices
- Private Corpporation
- Ecommerce
Use Cases
- Customer Reviews Analysis
- News Analysis
- Comment Analysis in Social Media, more…..
What is the Sentiment Analysis Data look like?
“यस्तै पोष्ट देखेपछि दिमाग तातिन्छ”, 0
“जन्म दीनको लाखौ करोडौ सुभकामना”, 1
“खुलेयाम घुमी रहेका छन”, 2
