کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11028865 | 1646701 | 2019 | 32 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Hierarchical viewpoint discovery from tweets using Bayesian modelling
ترجمه فارسی عنوان
کشف دیدگاه سلسله مراتبی از تویت ها با استفاده از مدل سازی بیزی
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کلمات کلیدی
پردازش زبان طبیعی، نظر معادن، مدل سازی بیزی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
When users express their stances towards a topic in social media, they might elaborate their viewpoints or reasoning. Oftentimes, viewpoints expressed by different users exhibit a hierarchical structure. Therefore, detecting this kind of hierarchical viewpoints offers a better insight to understand the public opinion. In this paper, we propose a novel Bayesian model for hierarchical viewpoint discovery from tweets. Driven by the motivation that a viewpoint expressed in a tweet can be regarded as a path from the root to a leaf of a hierarchical viewpoint tree, the assignment of the relevant viewpoint topics is assumed to follow two nested Chinese restaurant processes. Moreover, opinions in text are often expressed in un-semantically decomposable multi-terms or phrases, such as 'economic recession'. Hence, a hierarchical Pitman-Yor process is employed as a prior for modelling the generation of phrases with arbitrary length. Experimental results on two Twitter corpora demonstrate the effectiveness of the proposed Bayesian model for hierarchical viewpoint discovery.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 116, February 2019, Pages 430-438
Journal: Expert Systems with Applications - Volume 116, February 2019, Pages 430-438
نویسندگان
Lixing Zhu, Yulan He, Deyu Zhou,