TJP: Using Twitter to Analyze the Polarity of Contexts
Tawunrat Chalothorn, Jeremy Ellman · Northumbria Research Link (Northumbria University) · 2013
This paper presents our system, TJP, which participated in SemEval 2013 Task 2 part A: Contextual Polarity Disambiguation. The goal of this task is to predict whether marked contexts are positive, neutral or negative. However, only the scores of positive and negative class will be used to calculate the evaluation result using F-score. We chose to work as ‘constrained’, which used only the provided training and development data without additional sentiment annotated resources. Our approach considered unigram, bigram and trigram using Naive Bayes training model with the objective of establishing a simpleapproach baseline. Our system achieved Fscore 81.23% and F-score 78.16% in the results for SMS messages and Tweets respectively.