多个平行短语建议对本族语和非本族语英语写作者电子邮件输入和写作行为的影响
The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers
摘要：
我们提出了一个深入的分析，从神经语言模型对用户行为的输入和文本组成的电子邮件写作的多字建议的选择的影响。我们的研究第一次比较了不同数量的平行建议，并使用母语和非母语的英语作家，探索权衡“效率与思维”，出现在最近的文献。我们用神经语言模型（GPT-2）构建了一个文本编辑器原型，并在30人的预研究中进行了改进。在一项在线研究（N=156）中，人们在四种情况下（0/1/3/6平行建议）撰写电子邮件。我们的研究结果揭示了：（1）当建议多个短语时，构思的好处和效率的成本;（2）非母语人士从更多的建议中受益更多;（3）对行为模式的进一步洞察。我们讨论了对研究的影响，交互式建议系统的设计，以及用人工智能支持作家而不是取代他们的愿景。
英文摘要：
We present an in-depth analysis of the impact of multi-word suggestion choices from a neural language model on user behaviour regarding input and text composition in email writing. Our study for the first time compares different numbers of parallel suggestions, and use by native and non-native English writers, to explore a trade-off of "efficiency vs ideation", emerging from recent literature. We built a text editor prototype with a neural language model (GPT-2), refined in a prestudy with 30 people. In an online study (N=156), people composed emails in four conditions (0/1/3/6 parallel suggestions). Our results reveal (1) benefits for ideation, and costs for efficiency, when suggesting multiple phrases; (2) that non-native speakers benefit more from more suggestions; and (3) further insights into behaviour patterns. We discuss implications for research, the design of interactive suggestion systems, and the vision of supporting writers with AI instead of replacing them.
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。
