• Journal of Families and Better Life
• /
• v.24 no.1 s.79
• /
• pp.31-41
• /
• 2006

This study was to investigate differences in peer attachment, emotion regulation style and depression perceived by adolescents according to age and gender of adolescents. Also, aim that identifies variables which have influences on adolescents' depression. The subjects were 2279 middle and high school students(male 1150, female 1129) who live in Seoul and Kyonggi. All respondents answered by self-report questionnaire. The scales of emotion regulation style consist of three parts: support-seeking, avoidance/distraction, and active problem-solving. Data were analyzed by two-way ANOVA, t-tset and stepwise multiple regression. The major findings were as follows. First, older male and female adolescents perceived less peer attachment than younger adolescents. Specially female adolescents showed more differences between older adolescents and younger adolescents. Second, male adolescents showed more avoidance/distraction style and active problem-solving style but less support-seeking style than female adolescents. Third, older adolescents perceived more depression than younger adolescents. Fourth, peer attachment, age, avoidance/distraction style, active problem-solving style, support-seeking style and gender had a significant effect on adolescents' depression. In other words, adolescents who had more avoidance/distraction style and support-seeking style, who had less peer attachment and active problem-solving style, who had more avoidance/distraction style and support-seeking style, who had less peer attachment and active problem-solving style, who was older adolescents than younger adolescents, and who was female adolescents than male adolescents perceived more depression. The study results suggest that the degree of peer attachment was the most powerful predictor of adolescents' depression.

• The Journal of the Korea Contents Association
• /
• v.15 no.4
• /
• pp.545-555
• /
• 2015

We investigated the influence of negative emotion such as state-trait anxiety and depression and working memory (WM) on Foreign Language Vocabulary Learning (FLVL) of South Korean university students. Also, its implications for developing contents for FLVL were discerned. To do so, state-trait anxiety and depression inventories as well as four kinds of WM test were performed for 132 undergraduate students. Participants also had two semantic learning sessions for Swahili words. The mean scores of negative emotions were normal level. The results of structural equation modeling (SEM) showed that there was no effect of negative emotion on FLVL, while direct effects of the negative emotion on WM and the WM on FLVL were significant. Such results suggested that FLVL would be weakened, with the result that WM had been impaired by negative emotions. These outcomes suggested that when developing FLVL content for university students, it is necessary to consider the negative emotions of foreign language learners and to develop the contents for FLVL in the light of WM load.

• Journal of Korea Game Society
• /
• v.12 no.6
• /
• pp.131-144
• /
• 2012

To affect users' attitudes on social issues, some serious games use narrative which can be an effective tool to provoke users' emotions. In this paper, focus group interview on the experiences about playing was conducted to figure out if the parts of narratives containing educational goals can actually provoke certain emotions or not. From the interview, words having emotional meaning were extracted and matched with Korean Emotion Terms Database. Then the emotion terms were compared with Russell's schematic map of core affect and were categorized. The result showed that users mostly felt unpleasant emotions during the play. The unpleasant emotions helped to achieve the game's goal which is conveying the tragedy of war.

• Science of Emotion and Sensibility
• /
• v.20 no.1
• /
• pp.75-82
• /
• 2017

We propose a novel method for modeling emotional dimensions using expansion of Russell's (1980) emotional dimensions (Circumplex Model). The Circumplex Model represents emotional words in two axes (Arousal, Valence). However, other researchers have insisted that location of word in Russell's model which is expressed by single point could not represent exact position. Consequently, it is difficult to apply this model in engineering fields (such as Science of Emotion & Sensibility, Human-Computer-Interaction, Ergonomics, etc.). Therefore, we propose a new modeling method which expresses emotional word not as a single point but as a region. We conducted survey to obtain actual data and derived equations using ellipse formula to represent emotional region. Furthermore, we applied ANEW and IAPS which are commonly used in many studies to our emotional model using pattern recognition algorithm. Using our method, we could solve problems with Russell's model and our model is easily applicable to the field of engineering.

• Science of Emotion and Sensibility
• /
• v.15 no.4
• /
• pp.425-440
• /
• 2012

As the scale of the internet grows, the amount of subjective data increases. Thus, A need to classify automatically subjective data arises. Sentiment classification is a classification of subjective data by various types of sentiments. The sentiment classification researches have been studied focused on NLP(Natural Language Processing) and sentiment word dictionary. The former sentiment classification researches have two critical problems. First, the performance of morpheme analysis in NLP have fallen short of expectations. Second, it is not easy to choose sentiment words and determine how much a word has a sentiment. To solve these problems, this paper suggests a combination of using web-scale data and a statistical approach to sentiment classification. The proposed method of this paper is using statistics of words from web-scale data, rather than finding a meaning of a word. This approach differs from the former researches depended on NLP algorithms, it focuses on data. Hadoop and MapReduce will be used to handle web-scale data.

• Science of Emotion and Sensibility
• /
• v.13 no.4
• /
• pp.647-658
• /
• 2010

The purpose of the present study was to investigate the effects of self-regulated neurofeedback training on elementary school students' recall and recognition performance. For this purpose, the participants were randomly allocated to control condition where no training was provided or training condition where participants were trained in 4 self-regulated neurofeedback training sessions. As the dependent measures, correct free, recall rates and correct recognition rates were analyzed. The results showed that overall scores of recall and recognition were enhanced by the administration of the training itself, and as the training sessions advanced. In particular, the effect of the training seemed to induce more positive effect on the both memory tasks when the task difficulty (manipulated by increasing the number of target words) was increased. These results implied that self-regulated neurofeedback training can induce increased recollection ability for words by enhancing attentional process.

• Science of Emotion and Sensibility
• /
• v.4 no.2
• /
• pp.69-77
• /
• 2001

Positively biased asymmetry between positive and negative cognition is the basic assumption of heuristic human functioning. This article describes the SOM(states of mind) model for emotional judgement, a psycho-mathematical model built on affective-cognitive assessment research on the balance of positive and negative thoughts and feelings. The SOM model suggests that subjects on the average choose a positive over a negative pole with the probability 0.62 and the precise value of this constant coincides with algebraic “golden section” 　.618:.382. Statistical analyses of 32 normal subjects shows that the mean of SOM ratios of self-referent judgement and incidental recall task for positive/negative emotional words are .62(SD=.08) and .58(SD=.4). Also, the SOM ratios are significantly correlated with self-referent judgement for positive/negative emotional words. Implications of cognitive balance and future research directions for emotional science are discussed.

• Archives of design research
• /
• v.18 no.1 s.59
• /
• pp.69-80
• /
• 2005

So far, there have been mary studies on human emotions and the emotional side of products in the field of emotional engineering. Contemporary emotion-related researches have focused mainly on the relationship between product aesthetics and the emotional responses elicited by the products, but little is known about emotions elicited from using the products. In this study we have extracted some emotional words that can come up during user interaction with a product and reveal emotional changes. Firstly, we assembled a set of emotional words that were sufficient to represent a general overview of Korean emotions, collected from various literature studies in the field of psychology, linguistics, emotional engineering. Secondly, we found emotional words from collecting user opinion on the website. In this study, we used heavy traffic websites such as shopping mall and mania sites. Finally the emotional words were collected from verbal protocols by using Think Aloud technique. The collected words were integrated according to standards and they were applied on evaluation survey twice for evaluating their appropriateness. This survey was conducted for identification of emotional expressions while using a product. Finally, we extracted 88 emotional words for measuring user's emotions expressed while using products. And we categorized the 88 words to form 6 groups by using factor analysis. The 6 categories that were extracted as a result of this study, such as aesthetics, satisfaction in usability, novelty, uncomfortable- ness, pleasure and excellence were found to be user's representative emotions expressed while using products. It is expected that emotional words and user's representative emotions extracted in this study will be used as subjective evaluation data that is required to measure user's emotional changes while using a product.

• Korean Journal of Cognitive Science
• /
• v.25 no.4
• /
• pp.385-416
• /
• 2014

In this study, memory for emotional words was compared between extraverts and introverts, employing signal detection analysis to distinguish differences in discriminative memory and response bias. Subjects were presented with a study list of emotional words in an encoding session, followed by a recognition session. Effects of task difficulty were examined by varying the nature of the encoding task and the intervals between study and test. For an easy task, with a retention interval of 5 minutes (Study I), introverts exhibited better memory (i.e., higher d') than extraverts, particularly for low-frequency words, and response biases did not differ between these two groups. For a difficult task, with a one-month retention period (Study II), performance was poor overall, and only high-frequency words were remembered; also extraverts adopted a more liberal criterion for 'old' responses (i.e., more hits and more false alarms) for positive emotional-valence words. These results suggest that as task difficulty drives down performance, effects of internal control processes become more apparent, revealing differences in response biases for positive words between extraverts and introverts. These results show that extraversion can distort memory performance for words, depending on their emotional valence.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2002.05a
• /
• pp.266-269
• /
• 2002

This paper explores a fundamental study of acquiring the users' KANSEI information regarding the recognition of shape models. Since there are many differences such as background differences and knowledge differences among users, they will produce different evaluations based on their KANSEI even when an identical shape model is presented. Cluster analysis is proved to be available for catching a group tendency and for constructing a mapping relation between a description of the shape model and the HANSEl database. In order to investigate an analogical relation and a mutual influence in our consciousness, first, we made a questionnaire that asked subjects to represent images having different colors and shape cones by using 4 pairs of adjectives (KANSEI words). Next, based on the cluster analysis of the questionnaire using a fuzzy set theory, we proposed a hypothesis showing how the analogical relation and the mutual influence work in our mind while viewing the shape models. Furthermore, how the properties of KANSEI depend on their descriptions was also investigated by virtue of the cluster analysis. This work will be valuable to construct a personal KANSEI database regarding the Shape Model Processing System.