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Profiling users via their reviews: an extended systematic mapping study
Software and Systems Modeling ( IF 2 ) Pub Date : 2020-03-19 , DOI: 10.1007/s10270-020-00790-w
Xin Dong , Tong Li , Rui Song , Zhiming Ding

With the extensive development of big data and social networks, the user profile field has received much attention. User profiling is essential for understanding the characteristics of various users, contributing to better understanding of their requirements in specific scenarios. User-generated contents which directly reflect people’s thoughts and intention are a valuable source for profiling users, among which user reviews by nature are invaluable sources for acquiring user requirements and have drawn increasing attention from both academia and industry. However, review-based user profiling (RBUP), as an emerging research direction, has not been systematically reviewed, hindering researchers from further investigation. In this work, we carry out a systematic mapping study on review-based user profiling, with an emphasis on investigating the generic analysis process of RBUP and identifying potential research directions. Specifically, 51 out of 2478 papers were carefully selected for investigation under a standardized and systematic procedure. By carrying out in-depth analysis over such papers, we have identified a generic process that should be followed to perform review-based user profiling. In addition, we perform multi-dimensional analysis on each step of the process in order to review current research progress and identify challenges and potential research directions. The results show that although traditional methods have been continuously improved, they are not sufficient to unleash the full potential of large-scale user reviews, especially the use of heterogeneous data for multi-dimensional user profiling.



中文翻译:

通过评论对用户进行分析:扩展的系统制图研究

随着大数据和社交网络的广泛发展,用户配置文件领域受到了广泛关注。用户配置文件对于了解各种用户的特征至关重要,有助于更好地了解他们在特定情况下的需求。用户生成的内容直接反映了人们的思想和意图,是描述用户的宝贵资源,其中,用户评论本质上是获取用户需求的宝贵资源,并引起了学术界和行业的越来越多的关注。但是,基于审查的用户配置文件(RBUP)作为一种新兴的研究方向,尚未得到系统地审查,从而阻碍了研究人员进行进一步的研究。在这项工作中,我们对基于评论的用户配置文件进行了系统的制图研究,重点是调查RBUP的通用分析过程并确定潜在的研究方向。具体而言,从2478篇论文中精心挑选了51篇进行标准化和系统化的研究。通过对此类论文进行深入分析,我们确定了执行基于审阅的用户配置文件时应遵循的通用过程。此外,我们在流程的每个步骤上执行多维分析,以便回顾当前的研究进展并确定挑战和潜在的研究方向。结果表明,尽管传统方法已得到不断改进,但它们不足以释放出大规模用户评论的全部潜力,尤其是将异构数据用于多维用户配置文件的使用。在2478篇论文中,有51篇是通过标准化和系统的程序精心选择的。通过对此类论文进行深入分析,我们确定了执行基于审阅的用户配置文件时应遵循的通用过程。此外,我们在过程的每个步骤上执行多维分析,以便回顾当前的研究进展并确定挑战和潜在的研究方向。结果表明,尽管传统方法已得到不断改进,但它们不足以释放出大规模用户评论的全部潜力,尤其是将异构数据用于多维用户配置文件的使用。在2478篇论文中,有51篇是通过标准化和系统化的程序精心选择的。通过对此类论文进行深入分析,我们确定了执行基于审阅的用户配置文件时应遵循的通用过程。此外,我们在流程的每个步骤上执行多维分析,以便回顾当前的研究进展并确定挑战和潜在的研究方向。结果表明,尽管传统方法已得到不断改进,但它们不足以释放出大规模用户评论的全部潜力,尤其是将异构数据用于多维用户配置文件的使用。我们已经确定了执行基于审阅的用户配置文件应遵循的通用过程。此外,我们在流程的每个步骤上执行多维分析,以便回顾当前的研究进展并确定挑战和潜在的研究方向。结果表明,尽管传统方法已得到不断改进,但它们不足以释放出大规模用户评论的全部潜力,尤其是将异构数据用于多维用户配置文件的使用。我们已经确定了执行基于审阅的用户配置文件应遵循的通用过程。此外,我们在过程的每个步骤上执行多维分析,以便回顾当前的研究进展并确定挑战和潜在的研究方向。结果表明,尽管传统方法已得到不断改进,但它们不足以释放出大规模用户评论的全部潜力,尤其是将异构数据用于多维用户配置文件的使用。

更新日期:2020-04-22
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