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arXiv 2101.05786cs.CLcs.AI

Persuasive Natural Language Generation -- A Literature Review

MIT Center for Collective Intelligence(麻省理工学院集体智慧中心)

Sebastian Duerr, Peter A. Gloor

英文摘要:

This literature review focuses on the use of Natural Language Generation (NLG) to automatically detect and generate persuasive texts. Extending previous research on automatic identification of persuasion in text, we concentrate on generative aspects through conceptualizing determinants of persuasion in five business-focused categories: benevolence, linguistic appropriacy, logical argumentation, trustworthiness, tools and datasets. These allow NLG to increase an existing message's persuasiveness. Previous research illustrates key aspects in each of the above mentioned five categories. A research agenda to further study persuasive NLG is developed. The review includes analysis of seventy-seven articles, outlining the existing body of knowledge and showing the steady progress in this research field.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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