Özet:

Emotions, which are an integral part of communication, in different forms (speech, gestures, face expressions, etc.) It appears. On social media platforms, people express their feelings and thoughts with the most text sharing. The texts people share through social media give an idea about their emotional situations. Many studies have been conducted to show that the frequency of emotions is related to personality characteristics. Therefore, it is important to identify and reveal the emotions that are hidden in the messages shared on social media. The emotions that are hidden in the texts can be expressed by words-sentiment dictionaries. When we look at these dictionaries, the NRC Emotional Dictionary, which can make the maximum number of emotions, can expose 8 different emotions along with the positive and the negative. But keeping the emotions of people who reflect their emotions through the text limited to positive-negative or several different emotions often remains insufficient in personality detection. In this study, the positive-negative of the text to catch more emotions than shared texts (hope, anxiety, love, frustration, optimism, anger, fear, sadness, etc.) There are 38 NAYALex dictionaries that make different emotions. The NRC Emotional Dictionary and Plutchik's Psycho-Evolution Theory Dictionary each word consists of 6469 English words associated with at least one of 38 different emotions. By conducting a series of experiments on our data set of 10,000 different Instagram user sharing posts, we have shown the applicability and availability of our NAYALex dictionary. Compared to other (LIWC, EmoSenticNet, NRC, Empath) emotional dictionaries, our dictionary can identify the most comprehensive emotion with 24.7% for 154 emotions that Tiffany indicates.

Anahtar Kelimeler:

Özet:

Emotions, which are an integral part of communication, emerge in different ways (speech, gestures, facial expressions, etc.). On social sharing platforms, people express their feelings and thoughts mostly with textual shares. Textual sharings of people through social media give an idea about their emotional state.Many studies have been carried out showing that the frequency of emotions in personality inference is related to personality traits.Therefore, it is important to detect and reveal the emotions hidden in the messages shared on social media.Emotions are hidden in textual posts that people share via social media. It is crucial to detect and reveal the emotions hidden in the messages shared on social media. When we look at these lexicons, the NRC Emotion Lexicon, which can detect the greatest number of emotions, can reveal 8 different emotions in total, positive and negative. However, limiting the emotions of people who reflect their feelings through text to positive-negative or a few different emotions is often insufficient in personality determination. In this study, the NAYALex lexicon that can detect 38 different emotions (hope, anxiety, love, pessimism, optimism, anger, fear, sadness, etc.) from texts is proposed to recognize more emotions from shared texts. NRC Emotion Lexicon and each word of our lexicon, which we base on Plutchik'sPsychoevolutionary Theory of emotions, consists of 6469 English words associated with at least one of 38 different emotions. The applicability and usability of our NAYALexLexiconis demonstrated by conducting some experiments on our data set consisting of 10000 different posts belonging to Instagram users.Compared to other (LIWC, EmoSenticNet, NRC, Empath) emotion lexicons, our lexicon can detect the highest comprehensive emotion with 24.7% for the 154 emotions Tiffany stated.