# A Continuous Music Recommendation Method Considering Emotional Change
## 6 Experiments and Evaluation
### Experimental Data  
In this section, we describe the data used to demonstrate the effectiveness of the proposed method. The music data used in this study included emotional values, valence, and arousal data sourced from [PERSON] et al. [22]. The emotional numerical data of the music were classified into 13 types of emotions and stored as values ranging between 0 and 1. The valence and arousal data for the music ranged from one to nine.  
Based on the collected data, the procedures outlined in Sections 3.1 and 3.2 were conducted. Table 4 displays a subset of the refined data used in the experiments. The data were categorized by emotional area in the following order: happy, peaceful, angry, and sad.  
The user data used in this study were emotional history data sourced from [PERSON] et al. [13]. These data represent a survey of the emotions experienced by 12,212 users on specific days and times of the week. The user's emotional history data were classified into 18 emotions and stored as values of 1 or 0 by checking the emotions felt by the user. ID is the number of users; Day is a value between 1 and 7, where 1 starts from Monday and 7 represents Sunday; and Hours is a value based on 24 h.  
For experimental data, the 18 collected emotions were mapped onto the 4 emotions used in this study. Table 5 presents the results of mapping these 18 emotions to 4 emotions based on the standard word classification for emotion [50].  
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**No.** & **Emotion** & **Valance** & **Arousal** & **Happy** & **Angry** & **Sad** & **Peaceful** \\ \hline
1 & Angry & \(-0.5833\) & \(0.5833\) & \(0.3396\) & \(0.6604\) & \(0.0000\) & \(0.0000\) \\
2 & Happy & \(0.0833\) & \(0.0833\) & \(0.4504\) & \(0.1206\) & \(0.0000\) & \(0.4290\) \\
3 & Happy & \(0.5000\) & \(0.4167\) & \(0.5038\) & \(0.1145\) & \(0.0000\) & \(0.3817\) \\
4 & Peaceful & \(0.0833\) & \(-0.0833\) & \(0.0678\) & \(0.0282\) & \(0.4520\) & \(0.4520\) \\
5 & Peaceful & \(0.2500\) & \(-0.4167\) & \(0.1212\) & \(0.0303\) & \(0.2424\) & \(0.6061\) \\ \(\ldots\) & \(\ldots\) & \(\ldots\) & \(\ldots\) & \(\ldots\) & \(\ldots\) & \(\ldots\) \\
570 & Peaceful & \(0.7500\) & \(-0.2500\) & \(0.1109\) & \(0.1039\) & \(0.2771\) & \(0.5081\) \\ \hline \end{tabular}
\end{table}
Table 4: Part of the preprocessed data for emotion analysis of music.  
\begin{table}
\begin{tabular}{c c} \hline
**Emotion** & **Collected Emotions** \\ \hline Happy & Pride, love, gratitude, joy, awe, amusement, alertness \\ Anxiety, disdain, offense, guilt, disgust, fear, \\ embarrassment, anger \\ Sad & Sadness \\ Peaceful & Hope, satisfaction \\ \hline \end{tabular}
\end{table}
Table 5: Results of emotion mapping.  
Equation (22) was used to calculate the user's emotional level based on the classification results into the four primary emotions.  
\[E_{u,i}=\frac{\sum_{k=1}^{N_{i}}select_{i,k}}{\sum_{k=1}^{N}select_{k}}\ (i=1,2, \ldots,n) \tag{22}\]  
where \(E_{u,i}\) is the emotion \(i\) value of the user \(u\), \(select_{i,k}\) indicates whether the collected emotion axis \(k\) included in emotion \(i\) is selected, \(select_{k}\) indicates whether the collected emotion axis \(k\) is selected, \(i\) is the index of emotion \(i\), \(k\) is the index of collected emotions included in emotion \(i\), \(N_{i}\) represents the number of collected emotions included in emotion \(i\), and \(N\) represents the total number of emotions.  
Table 6 shows an example of the numerical data for each user emotion, classified into four categories. To analyze the user's emotions by time of day, data points without selected emotions at the given time were excluded. Additionally, user data with a history of regular intervals of days and times were selected for the experiment. Although there were limitations in selecting data from users who had emotional histories recorded at equal intervals, the experiment was conducted by setting the selection criteria according to the data distribution.