Readability of Twitter Tweets for Second Language Learners
Readability of Twitter Tweets for Second Language Learners
复制标题
Twitter 推文对于第二语言学习者的可读性
DOI：
--
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
A. Uitdenbogerd
中科院分区：
文献类型：
--
作者：
Patrick Jacob;A. Uitdenbogerd
通过阅读获得最佳语言习得需要学习者的阅读略高于其当前的语言技能水平。识别正确级别的材料是自动可读性测量的重要作用。 Twitter 等短信平台提供了语言练习的机会，同时阅读当前主题并进行少量对话，并且可以根据语言标准进行过滤以适合学习者。在这项研究中，我们探讨了推文对于英语学习者的可读性以及哪些因素有助于其可读性。我们针对来自 6 个语言组的参与者收集了 14,659 个数据点，每个数据点代表 4100 条推文池中的一条推文，以及对感知可读性的判断。传统的可读性测量和特征在数据集上失败了，但人口统计数据表明，判断在很大程度上是真实的，并且反映了报告的语言技能，这与其他最近的研究是一致的。我们报告数据集的属性以及对未来研究的影响。
Optimal language acquisition via reading requires the learners to read slightly above their current language skill level. Identifying material at the right level is the essential role of automatic readability measurement. Short message platforms such as Twitter offer the opportunity for language practice while reading about current topics and engaging in conversation in small doses, and can be filtered according to linguistic criteria to suit the learner. In this research, we explore how readable tweets are for English language learners and which factors contribute to their readability. With participants from six language groups, we collected 14,659 data points, each representing a tweet from a pool of 4100 tweets, and a judgement of perceived readability. Traditional readability measures and features failed on the data-set, but demographic data showed that judgements were largely genuine and reflected reported language skill, which is consistent with other recent studies. We report on the properties of the data set and implications for future research.