Multiview representation learning of data can help construct coherent and contextualized users' representations on social media. This paper suggests a joint embedding model, incorporating users' social and textual information to learn contextualized user representations used for understanding their lifestyle choices. We apply our model to tweets related to two lifestyle activities, `Yoga' and `Keto diet' and use it to analyze users' activity type and motivation. We explain the data collection and annotation process in detail and provide an in-depth analysis of users from different classes based on their Twitter content. Our experiments show that our model results in performance improvements in both domains.
翻译:本文建议采用一个联合嵌入模式,纳入用户的社会和文字信息,学习用于理解其生活方式选择的背景化用户的表述;我们运用我们的模式,在两种生活方式活动“Yoga”和“Keto 饮食”的推特上进行推文,并用来分析用户的活动类型和动机;我们详细解释数据收集和批注过程,并根据其推特内容对不同阶层的用户进行深入分析;我们的实验表明,我们的模型在改善这两个领域的绩效方面产生了结果。