AN INVESTIGATION OF THE EMOTIONAL DIMENSION IN SONGS SUNG BY NEŞET ERTAŞ: AN APPLICATION OF EMOTIONAL INDEX NEŞET ERTAŞ TÜRKÜLERİNDE DUYGULANIM BOYUTUNUN İNCELENMESİ: BİR DUYGULAR ENDEKSİ UYGULAMASI

This article aims to highlight the emotional characteristics of the lyrics and compositions of the folk songs sung by NeşetErtaş. For this purpose, the lyrics of 339 songs and the musical information of 264 compositions were crawled. There is alsoa speech among them. Three different sources have been used to obtain the lyrics and text of speech. Besides, an additionalprocess on to them has been applied; finally, verse-based or sentence-based texts have been obtained. In this process, thesetexts have been removed from certain words that do not have a meaning on their own, such as unnecessary punctuations,stopwords, onomatopoeic words, question suffixes, and transformed into a plain form. After this stage, verses or sentenceshave been made processable. First of all, to find the Turkish sentiments of each lyric, state-of-the-art machine learningtechniques have been applied to them, and the sentiment scores of each lyric have been computed. Three different machinelearning models have been used to calculate sentiment scores. These three different models are re-trained for the Turkishsentiments, which are of the models developed by Google. Only a single sentiment score has been obtained for each verseor sentence. The average of this sentiment score obtained from three different models has been calculated and used tosatisfy consistency. Afterward, a sentiment vector consisting of the verse of each song or each sentence of the speech texthas been created. The average of this sentiment vector is the overall score of that text (song or speech). The variance of thissentiment vector has also been calculated, in which this variance has been used to measure the sentiment tides in the songor speech text. Later, some valuable variables from a widely used music listening platform have been obtained as a basisfor composition information. Here, 10 variables named acousticness, danceability, energy, instrumentalness, liveness,loudness, speechiness, tempo, valence, popularity have been obtained. Three of them, danceability, energy, and valencevariables have been taken into account to estimate the emotional score of the composition by getting the average of thesethree variables. These scores are going to be matched then with the musical information of compositions of each uniquesong which are 169 intersectional sets of them, and an emotional map has been drawn statistically, which can be modeledwith the dimension of sentiments of lyrics and sentiments of composition showing Neşet Ertaş's emotional map. In the mapof emotions, the axes have been set in the range of (-1, +1). Therefore, the scores obtained for both texts and compositionshave been rescaled in the range of (-1, +1) with a formula generated for this purpose, which makes the scores of both textsand compositions are made comparable. After this stage, the sentiments of the texts are placed on the x-axis for the map ofemotions while composition sentiments are placed on the y-axis. On the x-axis, which is called the lyrics scale, a score of-1 is indicated by feelings of "sorrow", and a score of +1 is indicated by feelings of "happy". The composition scale, on theother hand, shows -1 score as “melancholic” and +1 score as “cheerful” on the y-axis. According to the results obtained, ithas been determined that the dominant characteristic of Neşet Ertaş's lyrics is based on sorrow words and that most of hisfolk songs are grouped in sorrowful lyrics and melancholic compositions. In addition, it has been found that his words arecharacterized by emotional changes and emotional tides; it has been also determined thanks to word cloud analysis that heoften has given humane and moral advice in phrases in the lyrics.Keywords: Neşet Ertaş, Sentiment Analysis, Sentiment Index, Machine Learning, Deep Learning.