The exploration of complex emotional states is a critical step in the development of the Sentivisor application. In this ongoing research, I am focusing on how six fundamental emotions—joy, fear, surprise, sadness, disgust, and anger—can combine to create a spectrum of more intricate emotional expressions. The table below represents a key part of this investigation, which was generated using AI, and reflects the complex interconnections between these emotions. This model is an important milestone in the progression of the Sentivisor application, providing deeper insights into emotional dynamics. By incorporating these findings into the Sentivisor platform, I aim to enhance the accuracy and personalization of emotional analysis, ultimately supporting mental well-being more effectively within the context of my application.
| Joy | Fear | Surprise | Sadness | Disgust | Anger | |
|---|---|---|---|---|---|---|
| Joy | Exhilaration | Nervousness | Delight | Bittersweet | Amusement | Frustration |
| Fear | Excitement | Anxiety | Shock | Despair | Aversion | Rage |
| Surprise | Delight | Fright | Astonishment | Sorrow | Aversion | Indignation |
| Sadness | Bittersweet | Despair | Sorrow | Grief | Disillusionment | Resentment |
| Disgust | Amusement | Aversion | Aversion | Disillusionment | Contempt | Contempt |
| Anger | Frustration | Rage | Indignation | Resentment | Disgust | Fury |
The table above reveals how fundamental emotions can combine to form more complex emotional states, offering a deeper understanding of emotional dynamics. For example, combinations like “joy + surprise” result in feelings of awe, while “anger + disgust” lead to contempt. These emotional blends highlight the nuanced ways in which emotions interact and influence one another.
This analysis underscores the importance of considering multiple emotional dimensions when assessing mental well-being. By understanding these complex emotional combinations, Sentivisor can provide more accurate and personalized insights, helping users better navigate their emotional landscapes. This model enhances the application’s ability to identify and interpret intricate emotional responses, which is essential for providing effective mental health support.