# E-Mail Network Patterns and Body Language Predict Risk-Taking Attitude
## 3 Results
### Body Sensor Results  
In this section, we demonstrate the predictive effect of the body signals on individuals' attitude towards the risk of Study B. The dependent variables are the mean and variance calculated from 4339 sensor records and 2450 affective records of 15 participants. Again, these variables show a strong correlation with the risk-preference scores in certain domains (see statistical description of the data and the Pearson coefficient between the body signals and the risk-preference in Supplementary Tables S3 and S4, respectively). Similar to Study A, we employ the OLS regression with these significant variables to predict the individuals' risk-preference. We report the OLS results of Study B in Table 4.  
We find that the sensor features can reliably distinguish high risk-preference individuals from low risk-preference ones. Specifically, the variability of the heart rate is found to be a significant indicator to measure one's risk-preference in the recreational domain. In addition, participants exhibiting a higher average heart rate show stronger willingness to take ethical risks. The acceleration-related variables also show a significant relationship  
Figure 2: Comparison between the predicted risk-preference score and the real self-reported value (\(N=34\)) in the general **(a,b)**, ethical (**c,d**), financial (**e,f**), health (**g,h**), recreational (**i,j**), and social domains (**k,l**). Each point corresponds to a specific participant. The predicted value is calculated by using significant predictors and the corresponding coefficients reported in Table 3.  
with risk-preference. For instance, the less consistent the body movement of a participant is (i.e., high variance of acceleration's magnitude), the more likely they will take risks in the ethical and health domains. Regarding the affective states, we find that participants with a more active sense of self are risk-seeking in financial activities. Finally, we compare the predicted values of the above variables with the real ones (see Figure 3). It can be seen that the statistics from sensor and mood data predict well in the general, financial, and recreational domains, while the prediction is comparatively poorer in the three other domains.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Dependent Var.** & **Significant Predictor (Coefficient)** & **Adj. \(R^{2}\)** & **RMSE** & **Chi-2 (Prob. \textgreater{} Chi-2)** \\ \hline \hline
1. general & var-AccX (0.41 **) & 0.33 & 0.42 & 1.53 (0.22) \\
2. ethical & var-AccX (0.47 **) & 0.18 & 0.67 & 1.67 (0.20) \\
3. financial & avg-active (1.73 **), var-AccY (-0.89 **) & 0.45 & 0.75 & 0.25 (0.62) \\
4. health & var-AccX (0.63 **) & 0.27 & 0.74 & 2.38 (0.12) \\
5. recreational & var-bpm (-0.54 **) & 0.50 & 0.88 & 1.08 (0.30) \\
6. social & avg-AccX (0.35 **) & 0.37 & 0.65 & 0.23 (0.63) \\ \hline \hline
**(b) Risk-willingness** & & & & \\ \hline
1. general & var-bpm (-0.55 **) & 0.49 & 0.90 & 0.95 (0.33) \\
2. ethical & avg-bpm (0.11 **) & 0.29 & 1.10 & 1.99 (0.16) \\
3. financial & avg-active (3.00 **), avg-AccY (-1.03 **) & 0.52 & 1.20 & 0.01 (0.95) \\
4. health & avg-AccY (-1.12 **) & 0.23 & 1.32 & 0.01 (0.93) \\
5. recreational & var-bpm (-0.87 **), avg-AccY (-0.82 *) & 0.60 & 1.33 & 0.35 (0.55) \\
6. social & avg-AccX (0.39 **) & 0.35 & 0.89 & 0.24 (0.62) \\ \hline \hline \end{tabular}
\end{table}
Table 4: OLS regression analysis of Study B based on 4339 sensor records and 2450 affective records from 15 participants. The stars within the bracket correspond to the predictor’s significance level: * \(p\) < 0.1, ** \(p\) < 0.05, *** \(p\) < 0.01.  
Figure 3: Comparison between the predicted risk-preference score and the realistic self-reported value (\(N=15\)) over six domains of Study B (**a,b** for general, **c,d** for ethical, **e,f** for financial, **g,h** for health, **i,j** for recreational, **k,l** for social). The predicted value is calculated using significant predictors and the corresponding coefficients reported in Table 4.