论文标题
社区问答平台上跨语言的任务偏好
Task Preferences across Languages on Community Question Answering Platforms
论文作者
论文摘要
随着社区问题回答（CQA）平台（例如Quora，Stackexchange和Wikihow）的稳定出现，用户现在可以毫无前所未有地访问有关各种查询和任务的信息。此外，跨越地理和语言界限的这些平台的快速扩散和本地化为研究不同社会语言群体中用户的任务要求和偏好提供了独特的机会。在这项研究中，我们实施了一个实体插入模型，该模型在大型的多语性和任务的问题和面向任务的问题 - 答案对的纵向数据集上进行了培训，以揭示和量化语言社区各种在线任务的（i）在这些社区中跨越任务流行的趋势的（II）在这些语言社区中的各种在线任务的普遍性和分布。我们的结果表明，任务偏好以及平台上语言社区之间的流行趋势存在很大差异。这项研究的发现将有助于Q＆A平台更好地为非英语用户提供策划和个性化内容，同时还为希望针对非英语社区在线的企业提供宝贵的见解。
With the steady emergence of community question answering (CQA) platforms like Quora, StackExchange, and WikiHow, users now have an unprecedented access to information on various kind of queries and tasks. Moreover, the rapid proliferation and localization of these platforms spanning geographic and linguistic boundaries offer a unique opportunity to study the task requirements and preferences of users in different socio-linguistic groups. In this study, we implement an entity-embedding model trained on a large longitudinal dataset of multi-lingual and task-oriented question-answer pairs to uncover and quantify the (i) prevalence and distribution of various online tasks across linguistic communities, and (ii) emerging and receding trends in task popularity over time in these communities. Our results show that there exists substantial variance in task preference as well as popularity trends across linguistic communities on the platform. Findings from this study will help Q&A platforms better curate and personalize content for non-English users, while also offering valuable insights to businesses looking to target non-English speaking communities online.
