• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.1
• /
• pp.32-41
• /
• 2023

Recently, many studies are being conducted to extract emotion from text and verify its information power in the field of finance, along with the recent development of big data analysis technology. A number of prior studies use pre-defined sentiment dictionaries or machine learning methods to extract sentiment from the financial documents. However, both methods have the disadvantage of being labor-intensive and subjective because it requires a manual sentiment learning process. In this study, we developed a financial sentiment dictionary that automatically extracts sentiment from the body text of analyst reports by using modified Bayes rule and verified the performance of the model through a binary classification model which predicts actual stock price movements. As a result of the prediction, it was found that the proposed financial dictionary from this research has about 4% better predictive power for actual stock price movements than the representative Loughran and McDonald's (2011) financial dictionary. The sentiment extraction method proposed in this study enables efficient and objective judgment because it automatically learns the sentiment of words using both the change in target price and the cumulative abnormal returns. In addition, the dictionary can be easily updated by re-calculating conditional probabilities. The results of this study are expected to be readily expandable and applicable not only to analyst reports, but also to financial field texts such as performance reports, IR reports, press articles, and social media.

• The Journal of the Korea Contents Association
• /
• v.18 no.7
• /
• pp.536-550
• /
• 2018

This paper examine how acceptance of AI robots can be achieved according to occupational groups when the discourse on human labor and occupation changes due to the new industrial revolution is spreading steadily. Previous research on the acceptance of new technologies and products has predicted use behavior through subjective beliefs and values that do not change well over the short term. Therefore, this study compares the beliefs, values, and use intention of AI robots according to occupation. As a result, the subjective belief factor for AI robots was classified into belief in rationality(reason) and belief in benevolence(emotion). The value factors were divided into acceptance value(role performance, communication, social comparison) and avoidance value(risk, complexity). There was a significant difference in the effect of these on the use intention of AI robot by occupation and employment types. This result suggests that there are gaps in the occupation group at the rate of technology acceptance, as opposed to the existing prediction that AI robots will be rapidly expanded by professionals.

• Korean journal of communication and information
• /
• v.69
• /
• pp.71-110
• /
• 2015

Beyond the technological behaviorism-oriented notion of prosumers, the current study explores the question of digital creative labour of the youth in the interrelated context of post-capitalist crisis and neoliberal ethos of selfhood. This analysis is situated particularly in the social conflicts and struggles in Korea, where the problems related to the precarization of the younger generation have been increasingly aggravated (in the realm of embodied reality) whereas their digital activities have been highly expressive (in the realm of mediated reality). The contradictions embedded in the question of the labour of the youth are delineated in the respect of the subjectivities of young free labour, or 'digital creative labour' in proposed terms: the precarious young free labour in Korea is the compound of social fragmentation, economic polarization, expansion of cognitive and emotion labour, boom of hedonistic consumerism, economic-cultural celebration of creativity and self-entrepreneurship, technological saturation of digital media, subjective/collective affects around excitement and ambition but also of anxiety and fear. The ambivalence and complexity of the young free labour is converged at the emergence of homo-economicus (Michel Foucault) through the subjectivation of the social (con)fusion of post-capitalist crisis and neoliberal governmentality of selfhood.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.1
• /
• pp.239-251
• /
• 2021

Traditional Chinese medicine has treated diseases and improved health in nature-based experience. Advanced nations began to be interested in naturopathic therapy in the late 19th century and it led China to research aromatherapy. This study searched previous researches related with aromatherapy and generally analyzed aroma oil, applied body parts, methods of use, and period of use. For research contents, scientific and society journals from 2000 to 2019 related with aromatherapy were searched in CNKI(www.cnki.com) and WANFANG DATE(www.wanfang.com). Finally, 30 papers were selected through 5-step qualitative evaluation and expert review and analyzed. Frequency and percentage(%) were calculated by means of the Excel 2013 Program and represented by a chart. The results of analyzing aromatherapy trends are as follows. All 30 papers were researched in the medical society. The most common symptom was irritation and anxiety that appeared in 13 papers. Lavender oil and bergamot oil were commonly used aroma oil. Commonly applied part and method were nose and nasal inhalation. For aroma oil associated with symptoms, lavender oil was the best in irritative, anxious, and negative emotion, depression, labor pain, sleep disorder, migraine, tension, and vomiting, pain, and fatigue after operation. Lemon, ginger, and peppermint oil was good for nausea. Based on the findings, this study derived applied body parts, methods of use, and period of use in aromatherapy. However, most aromatherapy was used for patients in the nursing and medical fields in the simple form of inhalation and local massage. This study will suggest a standard ground that aromatherapy is good for pain, colic pain, and tension in a short period but needs a long period for the efficacy of psychological and neurological symptoms.

• Journal of Intelligence and Information Systems
• /
• v.27 no.2
• /
• pp.55-78
• /
• 2021

Tosolve complex and diverse social problems and ensure the quality of life of individuals, social robots that can interact with humans are attracting attention. In the past, robots were recognized as beings that provide labor force as they put into industrial sites on behalf of humans. However, the concept of today's robot has been extended to social robots that coexist with humans and enable social interaction with the advent of Smart technology, which is considered an important driver in most industries. Specifically, there are service robots that respond to customers, the robots that have the purpose of edutainment, and the emotionalrobots that can interact with humans intimately. However, popularization of robots is not felt despite the current information environment in the modern ICT service environment and the 4th industrial revolution. Considering social interaction with users which is an important function of social robots, not only the technology of the robots but also other factors should be considered. The design elements of the robot are more important than other factors tomake consumers purchase essentially a social robot. In fact, existing studies on social robots are at the level of proposing "robot development methodology" or testing the effects provided by social robots to users in pieces. On the other hand, consumer emotions felt from the robot's appearance has an important influence in the process of forming user's perception, reasoning, evaluation and expectation. Furthermore, it can affect attitude toward robots and good feeling and performance reasoning, etc. Therefore, this study aims to verify the effect of appearance of social robot and consumer emotions on consumer's attitude toward social robot. At this time, a social robot design evaluation model is constructed by combining heterogeneous data from different sources. Specifically, the three quantitative indicator data for the appearance of social robots from the ABOT Database is included in the model. The consumer emotions of social robot design has been collected through (1) the existing design evaluation literature and (2) online buzzsuch as product reviews and blogs, (3) qualitative interviews for social robot design. Later, we collected the score of consumer emotions and attitudes toward various social robots through a large-scale consumer survey. First, we have derived the six major dimensions of consumer emotions for 23 pieces of detailed emotions through dimension reduction methodology. Then, statistical analysis was performed to verify the effect of derived consumer emotionson attitude toward social robots. Finally, the moderated regression analysis was performed to verify the effect of quantitatively collected indicators of social robot appearance on the relationship between consumer emotions and attitudes toward social robots. Interestingly, several significant moderation effects were identified, these effects are visualized with two-way interaction effect to interpret them from multidisciplinary perspectives. This study has theoretical contributions from the perspective of empirically verifying all stages from technical properties to consumer's emotion and attitudes toward social robots by linking the data from heterogeneous sources. It has practical significance that the result helps to develop the design guidelines based on consumer emotions in the design stage of social robot development.