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SentiWordNet for Indian Languages

机译:Santeworldnet为印度语言

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摘要

The discipline where sentiment/opinion/emotion has been identified and classified in human written text is well known as sentiment analysis. A typical computational approach to sentiment analysis starts with prior polarity lexicons where entries are tagged with their prior out of context polarity as human beings perceive using their cognitive knowledge. Till date, all research efforts found in sentiment lexicon literature deal mostly with English texts. In this article, we propose multiple computational techniques like, WordNet based, dictionary based, corpus based or generative approaches for generating SentiWordNet(s) for Indian languages. Currently, SentiWordNet(s) are being developed for three Indian languages: Bengali, Hindi and Telugu. An online intuitive game has been developed to create and validate the developed SentiWordNet(s) by involving Internet population. A number of automatic, semi-automatic and manual validations and evaluation methodologies have been adopted to measure the coverage and credibility of the developed SentiWordNet(s).
机译:在人文文本中确定和分类的教学/意见/情绪的纪律是众所周知的情绪分析。一种典型的情感分析方法从先前的极性词典开始,其中条目被标记为在上下文极性外,作为使用他们的认知知识感知的人类。到目前为止,情绪词典文学中发现的所有研究努力主要与英文文本交易。在本文中,我们提出了许多计算技术,如基于WordNet,字典的基于词典,基于语料库的或生成方法,用于为印度语言生成SentiwordNet。目前,SentiWordNet正在为三种印度语言开发:孟加拉,印地语和泰卢固。通过涉及互联网人口,开发了一个在线直观的游戏来创建和验证发达的SentiwordNet。已经采用了许多自动,半自动和手动验证和评估方法来衡量发达的SentiWordNet的覆盖范围和可信度。

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