تقرير
Using Argument-based Features to Predict and Analyse Review Helpfulness
| العنوان: | Using Argument-based Features to Predict and Analyse Review Helpfulness |
|---|---|
| المؤلفون: | Liu, Haijing, Gao, Yang, Lv, Pin, Li, Mengxue, Geng, Shiqiang, Li, Minglan, Wang, Hao |
| سنة النشر: | 2017 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | We study the helpful product reviews identification problem in this paper. We observe that the evidence-conclusion discourse relations, also known as arguments, often appear in product reviews, and we hypothesise that some argument-based features, e.g. the percentage of argumentative sentences, the evidences-conclusions ratios, are good indicators of helpful reviews. To validate this hypothesis, we manually annotate arguments in 110 hotel reviews, and investigate the effectiveness of several combinations of argument-based features. Experiments suggest that, when being used together with the argument-based features, the state-of-the-art baseline features can enjoy a performance boost (in terms of F1) of 11.01\% in average. Comment: 6 pages, EMNLP2017 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1707.07279 |
| رقم الأكسشن: | edsarx.1707.07279 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |