Incorporating Social Role Theory into Topic Models for Social Media Content Analysis
Incorporating Social Role Theory into Topic Models for Social Media Content Analysis
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DOI：
10.1109/tkde.2014.2359672
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发表时间：
2015-04
影响因子：
8.9
通讯作者：
Wayne Xin Zhao;Jinpeng Wang;Yulan He;Jian-Yun Nie;Ji-Rong Wen;Xiaoming Li
中科院分区：
文献类型：
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作者：
Wayne Xin Zhao;Jinpeng Wang;Yulan He;Jian-Yun Nie;Ji-Rong Wen;Xiaoming Li
在本文中，我们探讨了社会角色理论（SRT）的思想，并提出了一种新的正则化的主题模型，将SRT到社会媒体内容的生成过程。我们假设一个用户可以扮演多个社会角色，每个社会角色都可以履行不同的职责，并与潜在主题的角色驱动分布相关联。特别是，我们专注于与社交网络上最常见的社交活动相对应的社交角色。我们的模型在微博上实例化，即，Twitter和社区问答（cQA），即，耶！答案，Twitter上的社交角色包括“发起者”和“传播者”，cQA上的角色是“提问者”和“回答者”。用户之间的显式和隐式交互被考虑和建模为正则化因子。为了评估我们提出的方法的性能，我们在两个Twitter数据集和两个cQA数据集上进行了大量的实验。此外，我们还考虑多角色建模的科学论文，作者的研究专长领域被认为是一个社会角色。提出了一种基于多角色模型结果的主题关键词标注方法来检测用户研究兴趣的新应用。评价结果表明了该模型的可行性和有效性。
In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiated on microblogs, i.e., Twitter and community question-answering (cQA), i.e., Yahoo!Answers, where social roles on Twitter include “originators” and “propagators”, and roles on cQA are “askers” and “answerers”. Both explicit and implicit interactions between users are taken into account and modeled as regularization factors. To evaluate the performance of our proposed method, we have conducted extensive experiments on two Twitter datasets and two cQA datasets. Furthermore, we also consider multi-role modeling for scientific papers where an author's research expertise area is considered as a social role. A novel application of detecting users' research interests through topical keyword labeling based on the results of our multi-role model has been presented. The evaluation results have shown the feasibility and effectiveness of our model.