SentiMeter

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  Data Flow Diagram

SentiMeter – A tool for sentiment and emotion analysis

Introduction - Social media today is used by everyone, and keeping track of the competitors/fake users posting comments to spread negative sentiment about the brand becomes important to track. it’s also important to see what the genuine users are talking about the brand, whether they are happy with the product or whether there can be some areas of improvement. Constant monitoring helps any organization keep a check on their quality as well as quickly implement any potential improvements.

Objective - This tool helps in 2 things –

1. Analyse reactions and emotions on social media to detect cyber bullying

2. Monitor company reputation on social media and improve due diligence

Key features –

Sentiment analysis –

In this tool, the user can upload a csv with the text column to be classified. Once the file in the correct format is uploaded, the API is called. As an output the user gets to see the percentage distribution of negative and positive sentiments and also the most common occurring words for each of the sentiments in form of a word cloud. The text along with the sentiment score for each of the sentence can be downloaded in multiple formats as well.

Emotional traits –

In this part of the tool, the user can generate the keyword defining the emotion of the sentence. This output generated can be downloaded as well in multiple formats for further use.

Process Flow

1. The input data will be uploaded through User Interface. (https://nlp--hackathon.herokuapp.com/)

2. Process the input data using expert.ai NLP APIs to get the sentiments and emotional traits of the input and transformed based on sentiments and emotional traits.

3. The transformed data will be represented to the dashboard.

Built With

• django
• expertai
• html
• javascript
• python