TFG/TFM: Comparing Feature-Level Emotions Across Competing Mobile Apps

Motivation: Users often express emotions such as joy, sadness, or disappointment in app store reviews. Comparing these emotions across apps that offer similar features can provide valuable insights into user satisfaction and perceived quality. Understanding which features users react positively or negatively to can help developers identify strengths and weaknesses relative to competitors.

Objectives: This project aims to perform a comparative emotion analysis of mobile app reviews across several competing apps within the same domain (e.g., messaging or productivity). Using existing methods for feature extraction and emotion detection, the student will:

• Align semantically similar features across multiple apps.
• Analyze and visualize the distribution of emotions per feature per app.
• Identify which features generate more positive or negative emotions across competitors.

Expected Results:

• A dataset of feature-level emotions aligned across multiple apps.
• Comparative visualizations showing emotional differences between apps.
• Insights into which features are emotionally valued or criticized by users.