Mobile Application


Social Media Influencer App

  • A virtual assistant mobile app to assist celebrities in increasing their social media reach/influence on popular platforms.
  • Provide real time assistance while posting content by giving suggestions based on content sentiment, likely impact and upcoming events.
  • Generate influencer score based on user popularity.
  • Provide opportunities for brand association based on the range of influencer score.
  • Verify and validate 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 performed on 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 Tensor Flow.
  • Brand related goal/logo verification is performed by using image detection networks(FRCNN) based on Tensor Flow.
  • 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.
  • Notifications for android were performed using FireBase FCM, iOS using APNs and for the web Sockjs were used.
  • MongoDB
  • Amazon SQS
  • Sockjs
  • Firebase FCM
  • APNs
  • Amazon EC2
  • Open CV
  • TensorFlow
  • Python
  • Java
  • Amazon S3
  • Apache Spark
  • Amazon EMR
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