Added some documentation and changes to .senpy files.

affect/affect.senpy

@@ -14,14 +14,14 @@
         "sentiments-plugin": {
             "aliases": ["sentiplug"],
             "required": true,
-            "options": ["meaningCloud","sentiText","vaderSentiment"],
+            "options": ["sentiment-meaningCloud","sentiment-tass","sentiment-vader"],
-            "default": "sentiText"
+            "default": "sentiment-tass"
         },
         "emotions-plugin": {
             "aliases": ["emoplug"],
             "required": true,
-            "options": ["EmoTextWAF","EmoTextANEW"],
+            "options": ["emotion-wnaffect","emotion-anew"],
-            "default": "EmoTextANEW"
+            "default": "emotion-anew"
         },
         "endpoint": {
             "aliases": ["endpoint"],
@@ -36,5 +36,5 @@
 
 
     },
-    "requirements": {},
+    "requirements": {}
 }

emotion-wnaffect/README.md

@@ -0,0 +1,41 @@
+
+# WordNet-Affect plugin
+
+This plugin uses WordNet-Affect (http://wndomains.fbk.eu/wnaffect.html) to calculate the percentage of each emotion. The plugin classifies among five diferent emotions: anger, fear, disgust, joy and sadness. It is has been used a emotion mapping enlarge the emotions:
+
+- anger : general-dislike
+- fear : negative-fear
+- disgust : shame
+- joy : gratitude, affective, enthusiasm, love, joy, liking
+- sadness : ingrattitude, daze, humlity, compassion, despair, anxiety, sadness
+
+## Usage
+
+The parameters accepted are:
+
+- Language: English (en).
+- Input: Text to analyse.
+
+Example request: 
+```
+http://senpy.cluster.gsi.dit.upm.es/api/?algo=emotion-wnaffect&language=en&input=I%20love%20Madrid
+```
+
+Example respond: This plugin follows the standard for the senpy plugin response. For more information, please visit [senpy documentation](http://senpy.readthedocs.io). Specifically, NIF API section. 
+
+
+The response of this plugin uses [Onyx ontology](https://www.gsi.dit.upm.es/ontologies/onyx/) developed at GSI UPM for semantic web.
+
+This plugin uses WNAffect labels for emotion analysis.
+
+The emotion-wnaffect.senpy file can be copied and modified to use different versions of wnaffect with the same python code.
+
+
+## Known issues
+
+-  This plugin uses the pattern library, which means it will only run on python 2.7
+-  Wnaffect and corpora files are not included in the repository, but can be easily added either to the docker image (using a volume) or in a new docker image.
+ 
+![alt GSI Logo][logoGSI]
+
+[logoGSI]: http://www.gsi.dit.upm.es/images/stories/logos/gsi.png "GSI Logo"

emotion-wnaffect/README.rst

@@ -1,10 +0,0 @@
-This plugin uses WNAffect labels for emotion analysis.
-
-The emotion-wnaffect.senpy file can be copied and modified to use different versions of wnaffect with the same python code.
-
-
-Known issues
-============
-
-  * This plugin uses the pattern library, which means it will only run on python 2.7
-  * Wnaffect and corpora files are not included in the repository, but can be easily added either to the docker image (using a volume) or in a new docker image.

emotion-wnaffect/emotion-wnaffect.senpy

@@ -1,7 +1,7 @@
 {
     "name": "emotion-wnaffect",
     "module": "emotion-wnaffect",
-    "description": "Emotion classifier using rule-based classification.",
+    "description": "Emotion classifier using WordNet-Affect to calculate the percentage of each emotion. This plugin classifies among 6 emotions: anger,fear,disgust,joy,sadness or neutral. The only available language is English (en)",
     "author": "@icorcuera @balkian",
     "version": "0.2",
     "extra_params": {

sentiment-basic/sentiment-basic.senpy

@@ -1,7 +1,7 @@
 {
     "name": "sentiment-basic",
     "module": "sentiment-basic",
-    "description": "Sentiment classifier using rule-based classification for Spanish. Based on english to spanish translation and SentiWordNet sentiment knowledge.",
+    "description": "Sentiment classifier using rule-based classification for Spanish. Based on english to spanish translation and SentiWordNet sentiment knowledge. This is a demo plugin that uses only some features from the TASS 2015 classifier. To use the entirely functional classifier you can use the service in: http://senpy.cluster.gsi.dit.upm.es.",
     "author": "github.com/nachtkatze",
     "version": "0.1",
     "extra_params": {

sentiment-meaningCloud/sentiment-meaningCloud.py

@@ -13,7 +13,6 @@ class DaedalusPlugin(SentimentPlugin):
     def activate(self, *args, **kwargs):
         pass
 
-
     def deactivate(self, *args, **kwargs):
         self.close()
      

sentiment-meaningCloud/sentiment-meaningCloud.senpy

@@ -1,7 +1,7 @@
 {
-    "name": "meaningCloud",
+    "name": "sentiment-meaningCloud",
     "module": "sentiment-meaningCloud",
-    "description": "Sentiment analysis with meaningCloud service",
+    "description": "Sentiment analysis with meaningCloud service. To use this plugin, you need to obtain an API key from meaningCloud signing up here: https://www.meaningcloud.com/developer/login. When you had obtained the meaningCloud API Key, you have to provide it to the plugin, using param apiKey. Example request: http://senpy.cluster.gsi.dit.upm.es/api/?algo=meaningCloud&language=en&apiKey=<put here your API key>&input=I%20love%20Madrid.",
     "author": "GSI UPM",
     "version": "1.0",
     "extra_params": {
@@ -23,5 +23,6 @@
         }
 
     },
-    "requirements": {},
+    "requirements": {}
+
 }