Sentiment Analysis -FOD Field Offices Complaints and Reviews
Description
The AI solution helps USCIS Field Offices efficiently analyze and categorize large volumes of complaints by using machine learning to identify sentiment trends (positive, negative, or neutral) in public feedback.
Detailed example
A graph which categorizes the data into different sentiments using databricks dashboard to see how the customer service can be improved. Does not give any recommendation or decision.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
This system indicates the positive or negative feelings people express in their feedback to the U.S. Citizenship and Immigration Services (USCIS). Survey results categorized to specify the sentiments as positive negative or neutral tone in an excel dashboard.
Controls / human review
ATO: Not reported; PIA: Not published