The Infosys analytics team undertook multi-aspect sentiment analysis to make sense of passenger survey results. Our experts analyzed passenger satisfaction based on on-time arrival, in-flight service, and frequent flyer programs.
Infosys used the word embedding technique for textual analysis. We assigned sentiment polarity scores for each aspect of the passenger experience, and allocated weightage to crew members for consistency in their performance.
We leveraged Python for data analysis and Microsoft Power BI for data visualization.
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