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Social Media Influencer App
- A virtual assistant mobile app to assist celebrities in increasing their social media reach/influence on popular platforms.
- Provides real-time assistance while posting content by giving suggestions based on content sentiment, likely impact and upcoming events.
- Generates influencer score based on user popularity.
- Provides opportunities for brand association based on the range of influencer scores.
- Verify’s and validate’s brand-related goals performed by the user.
- Web dashboard/graphs to track the growth of user popularity and other stats.
- Bulk storage of raw data done in Amazon S3.S3 enables fast retrieval and provides advanced querying capabilities over bulk files.
- Analytics over raw data is performed on the Amazon EMR cluster using Apache Spark. Spark on EMR enables us to distribute the processing load across a cluster which can be scaled up/down based on the requirements.
- User content sentiment is predicted to be positive/negative/neutral with the help of models generated using TensorFlow.
- Brand-related goal/logo verification is performed by using image detection networks(FRCNN) based on TensorFlow.
- A Linear Regression Model is used to calculate the influencer score of each user based on various factors.
- MongoDB acts as a fast-serving layer to store the final results and provide fast querying capabilities to the application/dashboard.
- The Android notifications were handled using FireBase FCM, the iOS notifications were handled using APNs, and the web notifications were handled using Sockjs.
- Amazon SQS
- Firebase FCM
- Amazon EC2
- Open CV
- Amazon S3
- Apache Spark
- Amazon EMR