Mobile mood-tracking applications are increasingly used to help individuals understand their emotions and support mental well-being. Many existing Android-based mood diary apps allow users to record daily moods using text, emojis, or icons and display basic charts. However, most focus solely on mood logging and often lack features such as personalized suggestions, sentiment analysis, integration with daily routines, and robust data security. This paper presents the design of an Android-based Mood Diary and Daily Tracker application. The proposed system allows users to record moods through text, images, or voice notes and manage daily routines with a simple to-do list. A basic sentiment analysis approach is applied to classify moods into positive, neutral, or negative categories. Based on the classified mood, the app provides personalized suggestions related to diet, yoga, and healthy lifestyle habits. The system displays weekly and monthly mood trends using visual charts. User data security is ensured via Firebase Authentication and Firestore. The proposed application aims to encourage regular mood tracking, improve emotional self-awareness, and provide guidance for mental well-being. It will be evaluated on user interaction, effectiveness of mood tracking, and comparison with existing research, highlighting the benefits of an integrated mood diary system.
Dighe et al. (Fri,) studied this question.
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