EPJ Data Science

Table 2 Forecasting results

From: Activism via attention: interpretable spatiotemporal learning to forecast protest activities

	Charlottesville		Ferguson I		Ferguson II
	F-score	AUC	F-score	AUC	F-score	AUC
LR[tem]	0.200	0.696	0.103	0.733	0.343	0.752
LR[s,tem]	0.182	0.789	0.259	0.766	0.327	0.789
LR[s,tem,st]	0.200	0.734	0.230	0.722	0.314	0.773
SVM[tem]	0.200	0.818	0.000	0.791	0.400	0.816
SVM[s,tem]	0.186	0.809	0.000	0.796	0.408	0.837
SVM[s,tem,st]	0.000	0.782	0.000	0.754	0.313	0.780
LSTM	0.240	0.752	0.415	0.801	0.417	0.819
S + LSTM	0.267	0.778	0.423	0.804	0.439	0.838
S + LSTM (GL)	0.308	0.793	0.423	0.805	0.440	0.839
RMTFL	0.182	0.663	0.250	0.703	0.250	0.829
CMTFL-1	0.182	0.664	0.350	0.711	0.316	0.805
CMTFL-2	0.200	0.661	0.333	0.711	0.324	0.815
ActAttn (w/o GL)	0.308	0.830	0.459	0.820	0.464	0.849
ActAttn (w/o stAttn)	0.324	0.797	0.406	0.783	0.409	0.842
ActAttn (w/o spAttn)	0.333	0.836	0.448	0.812	0.448	0.846
ActAttn	0.400	0.843	0.462	0.822	0.471	0.853

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