Table 6.

F1-score values obtained by using Word2vec word representation method, with different parameters, of the KNN algorithm

		k=2	k=3	k=4	k=5	k=6	k=7	k=8
All	Manhattan	0.76	0.78	0.79	0.78	0.79	0.78	0.78
	Euclidean	0.76	0.79	0.79	0.78	0.79	0.78	0.8
	Minkowski	0.76	0.77	0.79	0.78	0.79	0.78	0.79
Topic-1	Manhattan	0.77	0.79	0.77	0.78	0.78	0.80	0.77
	Euclidean	0.77	0.78	0.78	0.77	0.77	0.78	0.78
	Minkowski	0.78	0.78	0.77	0.77	0.78	0.77	0.79
Topic-2	Manhattan	0.74	0.75	0.75	0.74	0.74	0.74	0.74
	Euclidean	0.75	0.75	0.75	0.74	0.75	0.74	0.75
	Minkowski	0.75	0.75	0.74	0.76	0.74	0.74	0.75
Topic-3	Manhattan	0.82	0.82	0.81	0.81	0.82	0.8	0.81
	Euclidean	0.81	0.81	0.77	0.82	0.82	0.82	0.81
	Minkowski	0.82	0.82	0.81	0.82	0.82	0.81	0.80