Lexicon-based Sentiment Analysis for Persian Text
Lexicon-based Sentiment Analysis for Persian Text
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基于词典的波斯语文本情感分析
DOI：
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发表时间：
2015
期刊：
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通讯作者：
M. H. Khodashahi
中科院分区：
文献类型：
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作者：
Fatemeh Amiri;S. Scerri;M. H. Khodashahi
与在线提供的产品和服务相关的大量客观和主观信息可用于为可能的新客户提供情境化建议和指导。用户在不同的购物网站、门户网站和社交媒体上留下的反馈和评论已经成为一种宝贵的资源，文本分析方法已经成为处理这类数据的无价工具。许多业务用例都应用了情感分析，以衡量人们对服务或产品的反应，或者支持客户在选择此类产品时做出决定。虽然这一领域的方法和技术很多，但大多数最多只能解决少数几种自然语言。在本文中，我们描述了一个基于词汇的情感分析方法设计的波斯语。对开发的GATE管道的评估显示，总体准确度高达69%。
The vast information related to products and services available online, of both objective and subjective nature, can be used to provide contextualized suggestions and guidance to possible new customers. User feedback and comments left on different shopping websites, portals and social media have become a valuable resource, and text analysis methods have become an invaluable tool to process this kind of data. A lot of business use-cases have applied sentiment analysis in order to gauge people’s response to a service or product, or to support customers with reaching a decision when choosing such a product. Although methods and techniques in this area abound, the majority only address a handful of natural languages at best. In this paper, we describe a lexiconbased sentiment analysis method designed around the Persian language. An evaluation of the developed GATE pipeline shows an encouraging overall accuracy of up to 69%.