Merge branch 'main' of https://gitlab.cci.drexel.edu/mjk488/sentiment-text-analysis

main.py

 # Mission: Create a sentiment analysis extention that will take the users text and determine whether or not it is inclusive.
-Depending on the users inclusivity it will display an approving/disapproving image.
+# Depending on the users inclusivity it will display an approving/disapproving image. 
 #
-Steps:
-Research Sentimental Analysis
--Textblob
-Create a Sentimental analysis program using Python
+# Steps:
+# Research Sentimental Analysis
+#   -Textblob
+# Create a Sentimental analysis program using Python
 #
-Research articles, hatespeech, etc... to use to train AI to determine what will be considered inclusive and exclusive.
-Use Libaray to train AI
+# Research articles, hatespeech, etc... to use to train AI to determine what will be considered inclusive and exclusive.
+# Use Libaray to train AI
 # 
 #
-Pseudocode
-Ask user for input (text from file/article/active typing)
-Import libraries (TextBlob)
-Libary (TextBlob) has API for tagging certain phrases
-Check whether or not the text includes tagged phrase
-If text includes tagged phrase, decrease the score
-If text includes no tagged phrases, increase the score
-Calculate the overall score of the user (difference)
-If score is positive then display image of happy cat
-If score is negitive then display image of angry cat
-If score is neutral (zero) then display image of middle cat
+# Pseudocode
+# Ask user for input (text from file/article/active typing)
+# Import libraries (TextBlob)
+# Libary (TextBlob) has API for tagging certain phrases 
+#   Check whether or not the text includes tagged phrase
+#   If text includes tagged phrase, decrease the score  
+#   If text includes no tagged phrases, increase the score
+#   
+# Calculate the overall score of the user (difference)
+#   If score is positive then display image of happy cat
+#   If score is negitive then display image of angry cat
+#   If score is neutral (zero) then display image of middle cat
+# 
+
 from textblob import TextBlob
 from newspaper import Article
 
@@ -37,3 +40,4 @@ print(text)
 blob = TextBlob(text)
 sentiment = blob.sentiment.polarity_# -1 to 1
 print(sentiment)
+