Benchmarking sentiment analysis methods for large-scale texts: A case for using continuum-scored words and word shift graphs.
Table S5: Ranked performance of dictionaries on the Movie Review corpus, broken into sentences.
['Rank', 'Title', '% Scored', 'F1 Trained of Scored', 'F1 Untrained of Scored', 'F1 Untrained, All']
The OL dictionary, with the highest performance classifying individual movie reviews of the 6 dictionaries tested in detail, performs worse than guessing at classifying individual sentences in movie reviews. Specifically, 76.9/74.2% of sentences in the positive/negative reviews sets have words in the OL dictionary, and of these OL achieves an F1-score of 0.44.