メールの未読でお困りですか?受信者をもっと感動させよう(Having problems with unread emails? Entice the recipients with more emotion)

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2025-05-23 ミシガン大学

ミシガン大学の研究によると、感情を込めた表現はメールの返信率を高める鍵となる。11.3百万通の公開メールを分析した結果、文体や社会的関係の強さが返信の有無に大きく影響することが判明。初回メールでは広い人脈が有利だが、過度な個人性や丁寧すぎる表現は逆効果の場合もある。対話が始まると、信頼や感情表現が継続的な返信に効果的。形式的すぎず、感情を伴った技術的表現も効果的とされる。研究成果はACL2025で発表。

<関連情報>

電子メールの反応を予測する言語的・社会的要因を因果的にモデル化する Causally Modeling the Linguistic and Social Factors that Predict Email Response

Yinuo Xu, Hong Chen, Sushrita Rakshit, Aparna Ananthasubramaniam, Omkar Yadav, Mingqian Zheng, Michael Jiang, Lechen Zhang, Bowen Yi, Kenan Alkiek, Abraham Israeli, Bangzhao Shu, Hua Shen, Jiaxin Pei, Haotian Zhang, Miriam Schirmer, David Jurgens
ACL Anthology  Published:2025
DOI:https://doi.org/10.18653/v1/2025.naacl-long.594

メールの未読でお困りですか?受信者をもっと感動させよう(Having problems with unread emails? Entice the recipients with more emotion)

Abstract

Email is a vital conduit for human communication across businesses, organizations, and broader societal contexts. In this study, we aim to model the intents, expectations, and responsiveness in email exchanges. To this end, we release SIZZLER, a new dataset containing 1800 emails annotated with nuanced types of intents and expectations. We benchmark models ranging from feature-based logistic regression to zero-shot prompting of large language models. Leveraging the predictive model for intent, expectations, and 14 other features, we analyze 11.3M emails from GMANE to study how linguistic and social factors influence the conversational dynamics in email exchanges. Through our causal analysis, we find that the email response rates are influenced by social status, argumentation, and in certain limited contexts, the strength of social connection.

1603情報システム・データ工学
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