• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.9
• /
• pp.381-390
• /
• 2022

Influenced by a culture that prefers non-face-to-face activity during the COVID-19 pandemic, chatbot usage is accelerating. Chatbots have been used for various purposes, not only for customer service in businesses and social conversations for fun but also for mental health. Chatbots are a platform where users can easily talk about their depressed moods because anonymity is guaranteed. However, most relevant research has been on social media data, especially Twitter data, and few studies have analyzed the commercially used chatbots data. In this study, we identified the characteristics of depressive discourse in user-chatbot interaction data by analyzing the chats, including the word 'depress,' using the topic modeling algorithm and the text-mining technique. Moreover, we compared its characteristics with those of the depressive moods in the Twitter data. Finally, we draw several design guidelines and suggest avenues for future research based on the study findings.

• Electronics and Telecommunications Trends
• /
• v.36 no.2
• /
• pp.93-101
• /
• 2021

The controversy over Artificial Intelligence (AI) chatbot "Iruda," which suspended its service 20 days after its launch, can be seen as the first case to inform the public of AI ethics issues. Based on this context, this study examines the controversy and social semantic formation of "Iruda" service cases using news topic modeling techniques. 963-news articles were used for the analysis, and the event's duration was analyzed based on major events, such as service start, controversy, and suspension, to understand the progress. From the analyses results, we obtain major keywords and a total of 16 topics (5, 4, 7) from the period. Finally, the implications for the development and utilization of AI services obtained through this controversy were discussed based on the analysis results.

• Asia pacific journal of information systems
• /
• v.33 no.4
• /
• pp.1058-1092
• /
• 2023

This study investigates the perception and adoption of ChatGPT (a large language model (LLM)-based chatbot created by OpenAI) among Korean users and assesses its potential as the next disruptive innovation. Drawing on previous literature, the study proposes perceived intelligence and perceived anthropomorphism as key differentiating factors of ChatGPT from earlier AI-based chatbots. Four individual motives (i.e., perceived usefulness, ease of use, enjoyment, and trust) and two societal motives (social influence and AI anxiety) were identified as antecedents of ChatGPT acceptance. A survey was conducted within two Korean online communities related to artificial intelligence, the findings of which confirm that ChatGPT is being used for both utilitarian and hedonic purposes, and that perceived usefulness and enjoyment positively impact the behavioral intention to adopt the chatbot. However, unlike prior expectations, perceived ease-of-use was not shown to exert significant influence on behavioral intention. Moreover, trust was not found to be a significant influencer to behavioral intention, and while social influence played a substantial role in adoption intention and perceived usefulness, AI anxiety did not show a significant effect. The study confirmed that perceived intelligence and perceived anthropomorphism are constructs that influence the individual factors that influence behavioral intention to adopt and highlights the need for future research to deconstruct and explore the factors that make ChatGPT "enjoyable" and "easy to use" and to better understand its potential as a disruptive technology. Service developers and LLM providers are advised to design user-centric applications, focus on user-friendliness, acknowledge that building trust takes time, and recognize the role of social influence in adoption.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.4
• /
• pp.9-14
• /
• 2024

This study developed a voice recognition chatbot system to address depression and loneliness among the elderly in an aging society. The system utilizes the Whisper model, GPT 2.5, and XTTS2 to provide high-performance voice recognition, natural language processing, and text-to-speech conversion. Users can express their emotions and states and receive appropriate responses, with voice recognition functionality using familiar voices for comfort and reassurance. The UX/UI design considers the cognitive responses, visual impairments, and physical limitations of the smart senior generation, using high contrast colors and readable fonts for enhanced usability. This research is expected to improve the quality of life for the elderly through voice-based interfaces.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2018.11a
• /
• pp.119-121
• /
• 2018

최근 자연어 처리 기술의 발전과 서비스 산업에서의 챗봇에 대한 수요가 증가함에 따라 챗봇을 활용한 서비스가 증가하고 있다. 본 논문은 챗봇을 이용한 소셜 매거진 생성 및 배포 시스템에 관한 것으로, 챗봇이 사용자들의 대화를 수집 및 분석하여 대화 주제와 키워드를 찾은 뒤, 크롤링 된 콘텐츠로부터 소셜 매거진을 생성 및 배포하는 서비스에 관한 것이다. 본 논문에서 제안한 시스템에 대한 성능은 실험을 통하여 검증하였다.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.19 no.4
• /
• pp.87-96
• /
• 2023

ChatGPT, a leader in generative AI, can use natural expressions like humans based on large-scale language models (LLM). The ability to grasp the context of the language and provide more specific answers by algorithms is excellent. It also has high-quality conversation capabilities that have significantly developed from past Chatbot services to the level of human conversation. In addition, it is expected to change the operation method of the tourism industry and improve the service by utilizing ChatGPT, a generative AI in the tourism sector. This study was conducted to explore ChatGPT trends and paradigms in tourism. The results of the study are as follows. First, keywords such as tourism, utilization, creation, technology, service, travel, holding, education, development, news, digital, future, and chatbot were widespread. Second, unlike other keywords, service, education, and Mokpo City data confirmed the results of a high degree of centrality. Third, due to CONCOR analysis, eight keyword clusters highly relevant to ChatGPT in the tourism sector emerged.

• Journal of Information Science Theory and Practice
• /
• v.12 no.2
• /
• pp.79-95
• /
• 2024

The new AI based conversational chatbot, ChatGPT, launched in November 2022, is causing a stir. There are many opinions about this being a 'threat or a promise,' and thus it is important to understand what has been said about this tool and, based on the growing literature that has emerged on the subject, demystify its effective impact on society. To analyse this impact, a systematic literature review with the support of the preferred reporting items for systematic reviews and meta-analysis protocol was used. The data, scientific documents, were collected using the main scientific databases - SCOPUS and Web of Science - and the results were presented based on a bibliometric and thematic exploration of content. The main findings indicate that people are increasingly using this chatbot in more diverse areas. Therefore, this study contributes at the practical level, aiming to enlighten people in general - both in professional and personal life - about this tool and its impacts. Also, it contributes at the theoretical level, which involves expanding understanding and elucidation of the impacts of ChatGPT in different areas of study.

• The Journal of Economics, Marketing and Management
• /
• v.6 no.1
• /
• pp.1-8
• /
• 2018

Purpose - Local social commerce market has grown up remarkably. And, Coupang has shown new delivery strategy of rocket delivery. Making new paradigm at local market, Coupang has expanded market scale. This study investigated state of local social commerce market, weight and promotion strategy of Coupang market to find out competitiveness edge of Coupang. Research design, data, and methodology - The study investigated state and concept of social commerce to find out state, problems and competitiveness of social commerce. New distribution service was short of precedent studies. Statistical analysis and experimental analysis were not used, and interview was done to investigate three of social commerce businesses. Results - CRM construction is insufficient to have poor system, Local delivery system could not be made enough at overnight delivery and customers were dissatisfied with ties with another company. Promotion shall be done by delivery system for increase of profitability, funding for more investment, chatbot to build new customer control system, and new delivery system to produce profit. Conclusions - Coupang and others have grown up rapidly to worsen profit and to jeopardize survival. Excessive initial investment has threatened the businesses, for instance, low sales of Amazon, excessive expenses, bench marking of logistics system, and others.

• Journal of Digital Convergence
• /
• v.20 no.3
• /
• pp.297-307
• /
• 2022

This study examined whether there was a difference in the attitude toward the recommended product and the effect on the choice deferral according to information sources. Experiment 1 examined the relationship between trust in information and product attitude, and between uncertainty and choice deferral according to information sources (AI chatbot vs. human). Experiment 2 examined the impact of social presence, perceived personalization, and choice deferral according to whether anthropomorphism of AI chatbots or not. The research results are as follows. First, consumers were found to have a more positive attitude toward products recommended by AI chatbots (vs. human). Second, consumers were more choice deferral whether to purchase products recommended by AI chatbots (vs. human). Third, it was found that consumers' selection of products recommended by anthropomorphic AI chatbots (vs. impersonated AI chatbots) increased. Also, the implications of this study and future research directions were discussed.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2022.11a
• /
• pp.836-838
• /
• 2022

반려동물 시장 및 동물 의료분야의 성장, 동물병원 이용 과정 개선의 필요성으로 반려동물 질병의 시작부터 끝까지 전 과정을 함께하는 원스탑 모바일 애플리케이션을 개발하였다. 증상으로 예상 질병을 진단하는 머신러닝 모델과 자연어 문장을 인식하는 딥러닝 챗봇으로 사용자가 편리하게 반려동물 이상 증상에 대한 예상 질병을 챗봇으로 상담할 수 있도록 구현하였다. 챗봇 시스템을 기반으로 '예상 진단', '질병백과', '문진표', '동물병원' 기능을 추가하여 일관된 기능들로 유기적인 서비스를 구성하였다.