INESC-ID: A Regression Model for Large Scale Twitter Sentiment Lexicon Induction
Silvio Amir, Ramón Fernández Astudillo, Wang Ling, Bruno Martins, Mário J. Silva, Isabel M. Trancoso · 2015
We present the approach followed by INESC-ID in the SemEval 2015 Twitter Sentiment Analysis challenge, subtask E. The goal was to determine the strength of the association of Twitter terms with positive sentiment.Using two labeled lexicons, we trained a regression model to predict the sentiment polarity and intensity of words and phrases.Terms were represented as word embeddings induced in an unsupervised fashion from a corpus of tweets.Our system attained the top ranking submission, attesting the general adequacy of the proposed approach.