文章基本信息

标题：A survey on sentiment analysis in Urdu: A resource-poor language
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作者：Asad Khattak ; Muhammad Zubair Asghar ; Anam Saeed 等
期刊名称：Egyptian Informatics Journal
印刷版ISSN：1110-8665
出版年度：2021
卷号：22
期号：1
页码：53-74
DOI：10.1016/j.eij.2020.04.003
出版社：Elsevier
摘要：Background/introduction The dawn of the internet opened the doors to the easy and widespread sharing of information on subject matters such as products, services, events and political opinions. While the volume of studies conducted on sentiment analysis is rapidly expanding, these studies mostly address English language concerns. The primary goal of this study is to present state-of-art survey for identifying the progress and shortcomings saddling Urdu sentiment analysis and propose rectifications. Methods We described the advancements made thus far in this area by categorising the studies along three dimensions, namely: text pre-processing lexical resources and sentiment classification. These pre-processing operations include word segmentation, text cleaning, spell checking and part-of-speech tagging. An evaluation of sophisticated lexical resources including corpuses and lexicons was carried out, and investigations were conducted on sentiment analysis constructs such as opinion words, modifiers, negations. Results and conclusions Performance is reported for each of the reviewed study. Based on experimental results and proposals forwarded through this paper provides the groundwork for further studies on Urdu sentiment analysis.
关键词：Urdu sentiment analysis ; Pre-processing ; Sentiment lexicon ; Datasets ; Corpus ; Urdu sentiment classification ; Semantic orientation