# Applying Spectral Clustering to Decode Mobility Patterns in Athens, Greece
## 4 Discussion  
### Clusters' Interpretation and Main Findings  
The six clusters showed diverse trip attributes. Socio-demographic characteristics of the travelers, who reported these trips, should be considered at this point. Table 3 presents sociodemographic characteristics and respective frequencies per cluster. In addition, a chi-square test was conducted to investigate the significance of relationships among the dummy variables. Initially, the first cluster could be titled \"an evening stroll nearby\", as it incorporates short-distance journeys performed by people who are probably not students, considering a 95% confidence interval. These trips predominantly occur during evening hours. Walking or riding the bus are the preferred transport modes. The second cluster that is the largest brought light about the commuting patterns of people whose job is in a close distance of their homes. A high and statistically significant share of them belong to the age group 50 to 65. They still prefer to travel by their private car, which is why the group is titled \"my work is nearby but I use my car\". The third pattern is called \"commuting by metro\". It concerns long-distance trips mainly to work performed by people who are not between 31 and 50 years old, as the chi-squared test revealed. A pattern that emerged from the fourth cluster concerns trips for work purposes, which, in contrast with the second pattern, have to do long distances. This pattern is mainly detected in the morning hours and the car are mostly chosen as the preferred mode of transport. This pattern predominantly includes economically active individuals with very high income. The fourth cluster can be titled as: \"my work is far away, so I have to use my car\". The fifth pattern that was revealed is characterized by \"trips of young people\" and it concerns midnight trips for recreation activities and morning trips from education at moderate distances, where increased use of public transport can be noted. This travel pattern is significantly composed of travelers aged 18-30 years old. Finally, the last pattern which emerged from the sixth cluster concerns movements to relatively short distances for other obligations, outside of work and education. In this pattern, balanced shares of car and public transport trips were reported. These trips are mainly made by elderly residents (65 or more years old). That is why is called \"other trips of inactive residents\". \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Cluster**} & **Preferred Transport Modes** & **Mean Trip Distance (Std. Dev)** & **Departure Time Period, 75\% of Trips** & **Main Trip** \\ \hline \multirow{2}{*}{Cluster 1} & Walking (41.7\%) & 1.68 km (\(\pm 1.17\)) & 16:00–22:00 & Home (50.9\%) \\  & Bus (23.1\%) & & & Recreation (48.1\%) \\ \hline \multirow{2}{*}{Cluster 2} & Car (47.4\%) & 2.70 km (\(\pm 1.82\)) & 07:00–11:00 & Work (35.4\%) \\  & Walking (16.6\%) & & & Recreation (20.6\%) \\ \hline \multirow{2}{*}{Cluster 3} & Train (44.6\%) & 14.04 km (\(\pm 7.46\)) & 07:00–20:00 & Home (50.4\%) \\  & Car (28.1\%) & & & Work (22.3\%) \\ \hline \multirow{2}{*}{Cluster 4} & Car (70.2\%) & 12.95 km (\(\pm 7.67\)) & 06:00–17:00 & Work (58.5\%) \\  & Train (14.6\%) & & & Home (13.8\%) \\ \hline \multirow{2}{*}{Cluster 5} & Train (40.5\%) & 10.60 km (\(\pm 9.35\)) & 00:00–12:00 & Home (56.1\%) \\  & Car (23.6\%) & & & Recreation (16.2\%) \\ \hline \multirow{2}{*}{Cluster 6} & Car (45.2\%) & 3.67 km (\(\pm 4.30\)) & 08:00–12:00 & Other (22.6\%) \\  & Train (21.0\%) & & & Recreation (21.0\%) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Main attributes of identified clusters. Regarding preferred transport modes, walking is directly associated with recreational trips. Additionally, most trips for educational purposes in Athens are carried out using public transport. Furthermore, shopping journeys are predominantly conducted on foot. Short-distance journeys are sometimes served by bus, while longer-distance trips are typically dominated by private car usage.