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This paper proposes a multidimensional text analysis approach combining Japanese NLP metrics and statistical methods to evaluate changes in risk disclosure quality, applied to Japan's 2019 corporate disclosure reforms. The analysis of 19,770 firm-year observations reveals complex shifts such as increased volume accompanied by decreased readability.
This paper analyzes longitudinal conversational trajectories of Bing Copilot users and compares them with WildChat data, finding that individual user habits are sticky and that WildChat overrepresents power users, challenging static views of user-LLM interactions.