Mood Maze

Catalog your emotions and uncover serenity

Strategy X DevHacks‘25

Track: Social Good

Beginner’s Track

Shraddha Pandey

Swetha Mohan

Clayton Wieberg

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The Problem

• Many people engage in self-reflection through journaling or diary writing, yet they find it difficult to interpret how their words connect to their emotions.
• Tracking emotional patterns is crucial for well-being, yet remains challenging.
• Existing mental health tools lack personalized insights from self-expression, making it difficult for individuals to recognize emotional trends over time.

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Solution – MoodMaze

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Novelty

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• Beyond Basic Emotion Rating: Unlike existing apps that only rate emotions, MoodMaze helps identify mood swings.
• Insightful Analysis: It goes a step further by analyzing the likely reasons behind each emotional judgment, helping users understand why they feel the way they do.

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Emotion Analysis

🧠 27 emotions including:

• 😢 Sadness
• 😡 Anger
• 😍 Admiration
• 🤗 Caring
• 😨 Fear
• 😇 Approval
• 🫠 Desire
• 🥺 Grief

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✍️ What it does:

• Analyze each sentence and predict emotion
• Combines sentence-level predictions into daily emotional summaries

⚡ Why this is cool:

• Works on real, paragraph-style writing
• Personalized and Automated
• Gives back helpful, digestible insights

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System Architecture

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User input

Journal

Preprocessing�Segmentation and text cleaning

Emotion Detection�Tokenization followed by the model and sigmoid activation

Insights Engine�Sentence level emotion display along with paragraph summary

Outputs and visualizations�Weekly bar graph visualization and

suggestions

Emotion Aggregation

Top emotion is selected per sentence, top 3 frequency is aggregated and displayed

Real-World Use

• Alternative to Personal Diary Writing: Offers a digital way to reflect on emotions.
• Parenting Support: Track child's emotional development.
• Tool for Psychologists: Can be integrated into therapy sessions for treatments.
• Mood-Based Decision Making: Mood based decision making leads to more mindful choices in daily life.

Demo

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Tech Stack

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Future Scope

• Multi-Modal Emotion Analysis: Enhance the model to process emotions from audio, video, and images for a more comprehensive understanding.

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• Social Media Integration: Implement emotion detection before posting to promote mindful interactions online.

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• Personalized Progress Tracking: Develop a system to monitor emotional trends and track the impact of suggested actions over time.