From 228eb6321b7e3eb21ce0fa73631d94ec90f120f4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?J=2E=20Fernando=20S=C3=A1nchez?= Date: Mon, 2 Sep 2019 12:03:37 +0200 Subject: [PATCH] update emotion-anew description --- emotion-anew/emotion-anew.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/emotion-anew/emotion-anew.py b/emotion-anew/emotion-anew.py index 8e9f5b7..d326070 100644 --- a/emotion-anew/emotion-anew.py +++ b/emotion-anew/emotion-anew.py @@ -24,7 +24,7 @@ from senpy.models import Results, EmotionSet, Entry, Emotion class ANEW(EmotionPlugin): - description = "This plugin consists on an emotion classifier using ANEW lexicon dictionary to calculate VAD (valence-arousal-dominance) of the sentence and determinate which emotion is closer to this value. Each emotion has a centroid, calculated according to this article: http://www.aclweb.org/anthology/W10-0208. The plugin is going to look for the words in the sentence that appear in the ANEW dictionary and calculate the average VAD score for the sentence. Once this score is calculated, it is going to seek the emotion that is closest to this value." + description = "This plugin consists on an emotion classifier using ANEW lexicon dictionary to calculate VAD (valence-arousal-dominance) of the sentence and determinate which emotion is closer to this value. Each emotion has a centroid, calculated according to this article: http://www.aclweb.org/anthology/W10-0208. The plugin is going to look for the words in the sentence that appear in the ANEW dictionary and calculate the average VAD score for the sentence. To obtain a categorical value (e.g., happy) use the emotion conversion API (e.g., `emotion-model=emoml:big6`)." author = "@icorcuera" version = "0.5.2" name = "emotion-anew"