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This work describes the identification and evaluation process of potential text markers for sentiment analysis. Evaluation of the markers and its use as part of the feature extraction process from plain text that is needed for sentiment analysis is presented. Evaluation of text marker obtained as a result of systematic analysis from a corpus over a second one allowed us to identify that emphasized positive words are strong indicators for positive text. The second corpus allowed us to evaluate the relation between the polarity of emphasized words and the text they appear in. Evaluation of the markers for polarity detection task in combination with a polarized dictionary produced polarity classification average precision of 56% using only three markers. This are promising results compared to the top 69% obtained using more features and specialized dictionaries for the same task.

Evaluation of Potential Spanish Text Markers on Social Posts as Features for Polarity Classification