We present the development of AffectPT-br, a new Brazilian Portuguese affective dictionary based on the LIWC 2015 English dictionary. LIWC dictionaries have been widely used in psychology and linguistics and there are versions of the dictionary in many languages, including Brazilian Portuguese (LIWC2007pt). We produced two text classification experiments with real datasets from social networks in order to compare AffectPT-br with LIWC2007pt. Results indicate AffectPT-br outperforms LIWC2007pt in the classification task with all classification algorithms we adopted.
When using this dictionary for academic purposes, please cite our article:
@INPROCEEDINGS{
AUTHOR="Flavio Carvalho and Gabriel dos Santos and Gustavo Paiva Guedes",
TITLE="AffectPT-br: an Affective Lexicon based on LIWC 2015",
BOOKTITLE="37th International Conference of the Chilean Computer Science Society (SCCC 2018)",
ADDRESS="University Andres Bello, Campus Antonio Varas, Santiago – Chile.",
DAYS="05-09",
MONTH="nov",
YEAR="2018",
ABSTRACT="Emotion detection is crucial in Human-Computer Interaction (HCI). Computers can never respond to individuals affective state if it cannot identify its emotion. Categorical approaches are commonly used for emotion detection in texts. It considers training models based on a set of affective states. Categorical approaches are often based on a dictionary that contains words associated with emotional categories. In this scenario, LIWC dictionaries have been widely used in psychology and linguistics. There are dictionaries in many languages, including Brazilian Portuguese (LIWC2007pt). This work focuses on the development of AffectPT-br, a new Brazilian Portuguese affective dictionary based on the LIWC 2015 English dictionary. We produced two text classification experiments with real datasets from social networks in order to compare AffectPT-br with LIWC2007pt. Results indicate AffectPT-br outperforms LIWC2007pt in the classification task with all classification algorithms we adopted.",
KEYWORDS="Natural Language Processing, Emotion Detection, Human Computer Interaction, LIWC",
}