Celebrity profiling through linguistic analysis of digital social networks

Computational Social Networks

Table 18 Model of the person’s characteristic Occupation

Group features	Variable	Religious		Science		Sports
	Predictor	Estimator	P-value	Estimator	P-value	Estimator	P-value
Lexical	(Intercept)	− 3.7	0.254	− 10.76	<0.001	5.8	<0.001
	V1	0.1	0.026	0.12	<0.001	− 0.11	<0.001
	V3	− 11.86	<0.001	− 7.56	0.156	− 1.15	0.211
	V4	− 0.03	0.965	2.02	<0.001	0.08	0.352
Syntactic	V14	− 1.82	0.157	− 0.37	0.253	− 1	<0.001
	V15	− 0.32	0.772	− 1.16	0.01	− 1.43	<0.001
	V16	− 4.74	0.007	− 4.79	<0.001	− 3.25	<0.001
	V17	6.74	<0.001	4.57	<0.001	− 1.27	0.002
	V18	− 0.01	0.947	− 0.01	0.76	-0.14	<0.001
Symbolic	V9	0.51	0.51	− 0.73	0.007	1.2	<0.001
Symbolic	V10	0.46	0.424	0.38	0.006	1.41	<0.001
Participation	V11	− 1.87	0.005	0.34	0.001	− 0.46	<0.001
Participation	V13	0.11	0.941	− 0.28	0.262	0.85	<0.001
Complementary information	V12	− 1.35	0.1	− 0.98	<0.001	− 4.47	<0.001
Residual deviance: 100703.9
AIC: 100913.9