Analysis of Indonesian sentiment text based on affective space model (ASM) using electroencephalogram (EEG) signals

The affective space model (ASM) based on the valence and arousal (VA) has been used by many researchers in determining the emotional state of an individual. Psychologist uses the self assessment maniquin (SAM) while other researchers uses the facial patterns, voice emotions and also electroencephalogram (EEG) signals to obtain the category of Sentiment analysis (SA) based on VA as the two dimensional approach represents affective state. However, getting affective words with VA scores are still infrequently used, even though these VA lexicon are advantageous resource in creating application of sentiment, especially in the Indonesian language and can be used as a corpus for SA. Thus this paper proposes to design and analyze Indonesian affective lexicons based on affective norm english word (ANEW) for automatic determination of VA rating of words. In this research, we proposed to develop an extensive number of sentiment states in Indonesian language that have been placed in terms of VA using SAM and would be correlated with EEG as a comprehensive tool of Neuro Physiological Signal for the emotion sentiment corpus rating.