• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.10
• /
• pp.3498-3512
• /
• 2021

This article describes how events that make up text stories can be represented and extracted. We also address the results from our simple experiment on extracting and clustering events in terms of emotions, under the assumption that different emotional events can be associated with the classified clusters. Each emotion cluster is based on Plutchik's eight basic emotion model, and the attributes of the NLTK-VADER are used for the classification criterion. While comparisons of the results with human raters show less accuracy for certain emotion types, emotion types such as joy and sadness show relatively high accuracy. The evaluation results with NRC Word Emotion Association Lexicon (aka EmoLex) show high accuracy values (more than 90% accuracy in anger, disgust, fear, and surprise), though precision and recall values are relatively low.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.11 no.4
• /
• pp.217-222
• /
• 2011

SNS is growing by leaps and bounds, and many users of SNS are using by a medium of communication. Using SNS users are using means of their own news and the change of emotional expression. In this study using emotional elements to the program was implemented to classify the message. Extraction of emotional elements were used for emotional vocabulary in OMLS (Ocean-Monmouth Legal Services). Emotional elements were extended by The Roget of the thesaurus and WordNet.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 1999.03a
• /
• pp.127-132
• /
• 1999

Cardiovascular, respiratory and electrodermal responses to acute stress episodes modeled by combined presentation of intense white noise and performance of word recognition task with noise background were studied in 15 college students. Experimental procedure consisted in sessions with white noise, word recognition task presentation with noise background and test with noise background. Recorded physiological variables were analyzed in terms of their sensitivity to detect activation of sympathetic and parasympathetic branches of autonomic nervous system and thus reflect autonomic arousal level during shout-term stress-inducing experimental manipulations. It was shown that performance of effortful mental task with noise background elicited significant physiological responses typical for active coping behavior, namely electrodermal arousal and increased cardiovascular activity. this response profile was more profound as compared to white noise only or attending task in noise background. However, all physiological responses were mostly phasic, without long-term tonic changes, since almost all variables recovered to their initial baseline levels, suggesting that dominant autonomic mechanisms in transient acute stress episodes were of parasympathetic nature (withdrawal in stress with subsequent activation in restoration period), while sympathetic contribution was not long-lasting. Nevertheless, increased number of stressors and their longer exposure may result in higher profile of tonic sympathetic arousal and reduced functional role of vagal mechanisms in autonomic balance regulation.

• Science of Emotion and Sensibility
• /
• v.22 no.2
• /
• pp.37-48
• /
• 2019

Current research explores the effect of language on the perception of facial emotion as suggested by the psychological construction theory of emotion by using a psychophysical method. In this study, we hypothesize that the perception of facial expression may be influenced if the observer is shown an affective word before he/she judges an expression. Moreover, we suggest that his/her understanding of a facial emotion will be in line with the conceptual context that the word denotes. During the two experiments conducted for this project, a control stimulus or words representing either angry or happy emotions were briefly presented to participants before they were shown a target face. These target faces were randomly selected from seven faces that were gradually morphed to show neutral to angry (in Experiment 1) and neutral to happy (in Experiment 2) expressions. The participants were asked to perform a two-alternative forced choice (2AFC) task to judge the emotion of the target face (i.e., decide whether it is angry or neutral, or happy or neutral). The results of Experiment 1 (when compared with the control condition) showed that words denoting anger decreased the point of subjective equality (PSE) for judging the emotion of the target as anger, whereas words denoting happiness increased the PSE. Experiment 2, in which participants had to judge expressions on a scale from happy to neutral, produced a contrasting pattern of results. The outcomes of this study support the claim of the psychological construction theory of emotion that the perception of facial emotion is an active construction process that may be influenced by information (such as affective words) that provide conceptual context.

• The Journal of Bigdata
• /
• v.5 no.1
• /
• pp.197-208
• /
• 2020

Lexical ambiguity means that a word can be interpreted as two or more meanings, such as homonym and polysemy, and there are many cases of word sense ambiguation in words expressing emotions. In terms of projecting human psychology, these words convey specific and rich contexts, resulting in lexical ambiguity. In this study, we propose an emotional classification model that disambiguate word sense using bidirectional LSTM. It is based on the assumption that if the information of the surrounding context is fully reflected, the problem of lexical ambiguity can be solved and the emotions that the sentence wants to express can be expressed as one. Bidirectional LSTM is an algorithm that is frequently used in the field of natural language processing research requiring contextual information and is also intended to be used in this study to learn context. GloVe embedding is used as the embedding layer of this research model, and the performance of this model was verified compared to the model applied with LSTM and RNN algorithms. Such a framework could contribute to various fields, including marketing, which could connect the emotions of SNS users to their desire for consumption.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.5
• /
• pp.586-591
• /
• 2008

This paper studied the emotion recognition system combined with robust speech recognition system in order to improve the performance of emotion recognition system. For this purpose, the effect of emotional variation on the speech recognition system and robust feature parameters of speech recognition system were studied using speech database containing various emotions. Final emotion recognition is processed using the input utterance and its emotional model according to the result of speech recognition. In the experiment, robust speech recognition system is HMM based speaker independent word recognizer using RASTA mel-cepstral coefficient and its derivatives and cepstral mean subtraction(CMS) as a signal bias removal. Experimental results showed that emotion recognizer combined with speech recognition system showed better performance than emotion recognizer alone.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2000.04a
• /
• pp.189-190
• /
• 2000

The purpose of this study is to estimate of design and ambience of goods by using 5 Kansei design items (shape, color, sense of material, fit, functionality/convenience). This paper describe that effectiveness of 5 Kansei design items. selecting image words and correspondence of 5 Kansei design items with image words. Kansei design items, selecting image words and correspondence of 5 Kansei design items with image words. (image words: the word describing about item image)

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 1998.04a
• /
• pp.81-88
• /
• 1998

두 문자열의 동일성 판단과 뇌파와의 관계가 탐색되었다. 피험자들은 컴퓨터의 화면에 나타나는 두 문자열의 동일성 여부를 판단하여 반응 키를 누르는 과제를 수행하였으며, 이화 동시에 피험자들의 뇌파가 기록되었다. 긍정 반응과 부정 반응 시의 뇌파를 비교한 결과, 좌측 전두엽 부위의 theta파, slow alpha파, fast alpha파 그리고 우측 전두엽 부위의 theta파 그리고 우측 전두엽 부위\ulcorner theta파 등이 긍부정 반응에 따라서 유의한 차이를 보였다.

• Journal of Contemporary Eastern Asia
• /
• v.13 no.2
• /
• pp.3-14
• /
• 2014

Online communities are an important source of electronic-word-of-mouth (eWOM), however few studies have examined these types of messages within the Middle Eastern context. This study focuses on Kuwaiti women as members of an online beauty forum; previous work has suggested a mediating effect of gender with women being more likely to trust and follow-up word-of-mouth with a purchase. A conceptual model, based on existing theoretical contributions, provides the basis of a coding framework for the message characteristics that influence members' eWOM adoption. A sub-set of the analysis is presented: 218 threads (1820 messages, coded into 6702 units) illustrating cases where eWOM was adopted and thereby demonstrating continuance intention with members returning to the forum. Content analysis revealed the prevalence of emotional aspects in messages, coded into a new category of 'community bonding'. Findings show that emotion expressed in messages is as influential and important as cognitive aspects of argument quality.

• Journal of Korean Library and Information Science Society
• /
• v.47 no.2
• /
• pp.51-70
• /
• 2016

The purpose of this study is to analyze the semantic relation network and valence-arousal dimension through the words that describe emotions in Korean language. The results of this analysis are summarized as follows. Firstly, each emotion word was semantically linked in the network. This particular feature hinders differentiating various types of "emotion words" in accordance with similarity in meaning. Instead, central emotion words playing a central role in a network was identified. Secondly, many words are classified as two categories at the valence and arousal level: (1) negative of valence and high of arousal, (2) negative of valence and middle of arousal. This aspects of Korean emotional words would be useful to analyze emotions in various text data of books and document information.