Research Article

Sentiment Analysis Using Common-Sense and Context Information

Algorithm 2

Finding ambiguous terms.
INPUT Polarity lexicon and training corpus
OUTPUT Ambiguous terms
(1) for Each WORD () in Polarity_Lexicon do
(2) = ((Positive_Count() * Positive_Score() − Negative_Count() * Negative_Score())
    ÷ (Positive_Count() + Negative_Count()))
(3) = ((((( − Positive_Score() * Positive_Count()) − ( − Negative Score()
     * Negative_Count()))/(Positive_Count() + Negative_Count())
(4) if   ≥ 0.75 then
(5)  Ambiguity = YES
(6)  Add to Ambiguous terms list
(7) else
(8)  Ambiguity = NO
(9)  Add to Polarity Lexicon
(10) end if
(11) end for