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Creating sentiment lexicon for sentiment analysis in Urdu: The case of a resource‐poor language

机译：在乌尔都语中创建用于情感分析的情感词典：资源贫乏的语言案例

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摘要

The sentiment analysis (SA) applications are becoming popular among the individuals and organizations for gathering and analysing user's sentiments about products, services, policies, and current affairs. Due to the availability of a wide range of English lexical resources, such as part-of-speech taggers, parsers, and polarity lexicons, development of sophisticated SA applications for the English language has attracted many researchers. Although there have been efforts for creating polarity lexicons in non-English languages such as Urdu, they suffer from many deficiencies, such as lack of publically available sentiment lexicons with a proper scoring mechanism of opinion words and modifiers. In this work, we present a word-level translation scheme for creating a first comprehensive Urdu polarity resource: "Urdu Lexicon" using a merger of existing resources: list of English opinion words, SentiWordNet, English-Urdu bilingual dictionary, and a collection of Urdu modifiers. We assign two polarity scores, positive and negative, to each Urdu opinion word. Moreover, modifiers are collected, classified, and tagged with proper polarity scores. We also perform an extrinsic evaluation in terms of subjectivity detection and sentiment classification, and the evaluation results show that the polarity scores assigned by this technique are more accurate than the baseline methods.
机译：情绪分析（SA）应用程序在个人和组织中变得越来越流行，用于收集和分析有关产品，服务，策略和时事的用户情绪。由于可以使用多种英语词汇资源，例如词性标记器，解析器和极性词典，因此针对英语的复杂SA应用程序的开发吸引了许多研究人员。尽管已经努力创建诸如乌尔都语之类的非英语语言的极性词典，但它们仍存在许多缺陷，例如缺乏公开的情感词典，它们没有适当的意见词和修饰语评分机制。在这项工作中，我们提出了一个词级翻译方案，用于使用现有资源的合并来创建第一个综合的Urdu极性资源：“ Urdu Lexicon”，包括英语见解词列表，SentiWordNet，英语-Urdu双语词典和乌尔都语修饰语的集合。我们给每个乌尔都语意见词分配两个极性分数，正负。而且，修饰剂被收集，分类并用适当的极性分数标记。我们还在主观性检测和情感分类方面进行了外部评估，评估结果表明，该技术分配的极性得分比基线方法更准确。

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