## 4 Results
### Notification Perception
#### 4.1.2 Cluster Analysis  
Cluster analysis was used in this diary study to organize the inputs from participants. Due to the large qualitative dataset, such an analysis method was implemented to arrange similar data together. Thus, in this case, the hierarchical cluster technique helped assist the analysis by synthesizing the qualitative text which had been noted in previous studies [46]. Such techniques have also been applied to assist the progress of exploring user behavior as well as experiences in the context of digital interventions within the health domain [47].  
We established this process by using the 15 unique labels derived from the initial analysis stage, representing distinct components in our dataset. In order to detect the optimal grouping, we conducted several variations of hierarchical clustering by testing a differing number of clusters to examine various potential groupings. From these iterations, we identified a four-cluster combination that was contextually the most meaningful concerning interpretability and thematic relevance. This particular clustering combination best represented the relationship between labels which allowed a clear and logical grouping.  
The four-cluster combination (see Figure 2) visually illustrates how the 15 labels are grouped based on their similarities. The red-outlined boxes that encompass the aforementioned labels represent each cluster.  
Figure 1: This figure illustrates an organized structure of labels that were acquired from the diary entries; notification-related labels, day characteristics-related labels, user-related labels.  
Cluster 1: The first cluster contains elements such as 'Ringer Off', 'Personal', 'Stressful', 'Work', and lastly 'Important'. This cluster presents factors that users explicitly mention their notifications were either personal or work-related. The aspect of stress being in this cluster represents a heightened mental tension stated by the participants. Importance has also been mentioned which indicates more relevant notifications are present in this group.  
Cluster 2: This cluster consists of three elements: 'Surprise', 'Urgent', and 'Tends to act quickly'. It characterizes situations or matters that appear abruptly and tend to require immediate attention or where instantaneous action is prioritized.  
Cluster 3: The third cluster accommodates three elements: 'Expected', 'Non-urgent', and 'Not Distracted'. It involves events or circumstances that are predictable and ones that do not require immediate attention nor interfere with tasks on hand.  
Cluster 4: The last cluster contains four elements: 'Irrelevant', 'Distracted', 'Relaxed', and 'Opt-out'. It likely characterizes situations that entail notifications with low importance. It depicts a sense of disengagement and low priority.  
Figure 3 represents the entire set of labels that fall under each corresponding cluster together with their count. Of the four clusters, each diary entry could produce 16 combinations. Each diary entry was assigned with the corresponding cluster given that at least 50% of that cluster's labels were mentioned. From there, it was apparent that 6 main characteristics were most prominent. Of the 423 labels, five statements did not contain sufficient data to link to any cluster.  
Figure 2: Figure of cluster analysis with the formation of 4 clusters.