Table 2 Description of the 38 users
From: Identifying and predicting social lifestyles in people’s trajectories by neural networks
User | Gender | Age | Profession | Status |
|---|---|---|---|---|
1 | Female | 24 | A student | Single |
2 | Male | 23 | A soldier | Single |
3 | Female | 24 | A student | Single |
4 | Male | 24 | A student | Single |
5 | Male | 25 | A student | In relationship |
6 | Male | 35 | A Ph.D candidate | Married + 3 |
7 | Male | 38 | A Ph.D candidate | Married + 1 |
8 | Female | 32 | An M.Sc. student | Married + 1 |
9 | Female | 27 | An M.Sc. student | Single |
10 | Male | 23 | A student | Single |
11 | Female | 27 | A teacher | Married + 1 |
12 | Male | 40 | A Ph.D candidate | Married + 1 |
13 | Male | 25 | A student | Single |
14 | Female | 60 | A pensioner | Married + 2 |
15 | Female | 24 | A student | Single |
16 | Male | 32 | A Ph.d | Single |
17 | Female | 40 | A teacher | Single + 2 |
18 | Female | 31 | A translator | Married |
19 | Male | 25 | A student | Single |
20 | Male | 26 | A student | Single |
21 | Male | 40 | A freelancer | Married + 2 |
22 | Male | 35 | An engineer | Married + 1 |
23 | Female | 44 | A manager | Married + 3 |
24 | Male | 32 | An engineer | Married + 1 |
25 | Female | 24 | A student | Single |
26 | Male | 27 | An M.Sc. student | Single |
27 | Female | 24 | A student | Single |
28 | Female | 30 | An engineer | In relationship |
29 | Male | 28 | A freelancer | Engaged |
30 | Female | 48 | An assistant professor | Married + 3 |
31 | Female | 33 | A medical doctor | Married + 1 |
32 | Male | 25 | A student | Single |
33 | Male | 26 | A student | Single |
34 | Male | 30 | An M.Sc. student | In relationship |
35 | Male | 26 | A student | Single |
36 | Male | 26 | A student | Single |
37 | Male | 26 | A student | Single |
38 | Male | 66 | A engineer | Married + 2 |