情绪分析

Larian M. Nkomo, Antonie Alm
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引用次数: 0

摘要

随着人们不断地在各种网络平台上表达自己,有大量的数据可以用于研究。在大多数情况下,这些数据是非结构化的,由于数据量大,分析起来可能会令人生畏。然而,情感分析等技术可以用来分析这些数据,并获得对研究人员有用的见解。没有在课堂上典型的学术和情感支持,非正式语言学习者控制自己的学习环境。本研究说明了情感分析如何被用于了解非正式二语学习者在与聊天机器人进行二语学习时的体验。数据是从各种在线平台收集的,以反映几年来使用四种具有聊天机器人功能的语言学习应用程序的经验。结果表明,非正式二语学习者对他们的经历有不同的看法,而情绪分析是分析非正式二语学习者定性数据的一种可行方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Analysis
With people constantly expressing themselves on various online platforms, there are multitudes of data available that can be used in research. In most cases, these data are unstructured and can be intimidating to analyse due to the large volumes. However, techniques such as sentiment analysis can be used to analyse these data and obtain insights that are useful for researchers. Without the academic and emotional support typically found in a classroom, informal language learners control their own learning environment. This study illustrates how sentiment analysis can be utilised to obtain insights on the experiences of informal L2 learners when they engage with chatbots for L2 learning. Data were collected from various online platforms to reflect experiences with four language learning applications with chatbot features over several years. Results suggest informal L2 learners have mixed sentiments on their experiences and sentiment analysis being a viable approach to analysing informal L2 learner qualitative data.
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