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Data Interview Question

Sentiment Evaluation on WallStreetBets

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Requirements Clarification & Assessment

  • Objective of the Model:

    • Clarify whether the model aims to predict the sentiment of specific stocks, the overall sentiment of the subreddit, or another objective.
    • Determine if the sentiment analysis is binary (positive/negative) or multi-class (positive, negative, neutral, etc.).
    • Understand how the sentiment analysis results will be utilized, particularly if they will influence investment decisions.
  • Data Requirements:

    • Ascertain access to historical data from the WallStreetBets subreddit.
    • Evaluate the availability, quality, and volume of data for training, validation, and testing.
  • Performance Constraints:

    • Identify any specific performance benchmarks (e.g., accuracy, latency) the model must meet.
    • Determine the frequency of retraining and prediction (e.g., real-time vs. batch processing).
  • Resources and Infrastructure:

    • Assess the computational resources required for developing, training, and deploying the model.
    • Consider the infrastructure needed for handling large volumes of data and ensuring model scalability.