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Haein Lee

Assistant Professor

Dongguk University

South Korea

Research Interests

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About

Haein Lee is an Assistant Professor at Dongguk University in South Korea. His research areas include sentiment analysis in cryptocurrency, user experience in educational applications, and the exploration of ESG signals through advanced machine learning models. Recent publications highlight his work on predicting Bitcoin prices and user satisfaction in AI applications, contributing to the fields of finance and technology.

Articles (19)

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2023

Collaborators (1)

Jang Hyun Kim

Sungkyunkwan University

SOUTH KOREA

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Haein Lee

Research Interests

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Articles (19)

The Governance-Experience Gap in Generative AI: A Cross-Level Analysis of Regulatory Frameworks and Interactional Frictions

Evaluating Software Quality in Cryptocurrency Wallet Applications: A User-Centered Approach Using ISO/IEC 25010:2011 Quality Model

Analysing Korean children's speech data for early childhood educational services: age-specific insights from text and audio analysis

LLM-Assisted and Rule-Based Assessment of ESG Disclosure Quality and Its Association with External ESG Ratings: Exploratory Evidence from S&P 500 Energy Firms

Semantic-Sentiment Fusion with Deep Learning: A Novel Framework for Hate Speech Detection

Simulating the people's voice: Leveraging algorithmic fidelity to assess ChatGPT's performance in modeling public opinion on Chinese government policies

Explainable zero-shot trading using multi-agent LLM architecture: A backtested approach for Bitcoin price

Detecting Bitcoin Sentiment: Leveraging Language Model Applications in Sentiment Analysis for Bitcoin Price Prediction

Analysis of UX Elements in Educational Applications for Young Children and Implementation of ISO/IEC 25010 Quality Standards

From corporate earnings calls to social impact: Exploring ESG signals in S&P 500 ESG index companies through transformer-based models

Refining the prediction of user satisfaction on chat-based AI applications with unsupervised filtering of rating text inconsistencies

Bitcoin Research in Business and Economics: A Bibliometric and Topic Modeling Review

Latent Profiles and Regression-Based Analysis of Socio-Emotional Development: Evidence from Longitudinal Data and Interpretable Machine Learning

Expansive data, extensive model: Investigating discussion topics around LLM through unsupervised machine learning in academic papers and news

Decoding Bitcoin: leveraging macro- and micro-factors in time series analysis for price prediction

Deep-learning-based stock market prediction incorporating ESG sentiment and technical indicators

CORRECT? CORECT!: Classification of ESG Ratings with Earnings Call Transcript

ESG2PreEM: Automated ESG grade assessment framework using pre-trained ensemble models

Comparing Social Media and News Articles on Climate Change: Different Viewpoints Revealed

Collaborators (1)

Jang Hyun Kim

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