The ever-increasing number of Internet users and online services, such as Amazon, Twitter and Facebook has rapidly motivated people to not just transact using the Internet but to also voice their opinions about products, services, policies, etc. Sentiment analysis is a field of study to extract and analyze public views and opinions. However, current research within this field mainly focuses on building systems and resources using the English language. The primary objective of this study is to examine existing research in building sentiment lexicon systems and to classify the methods with respect to non-English datasets. Additionally, the study also reviewed the tools used to build sentiment lexicons for non-English languages, ranging from those using machine translation to graph-based methods. Shortcomings are highlighted with the approaches along with recommendations to improve the performance of each approach and areas for further study and research.

越来越多的Internet用户和在线服务（例如Amazon，Twitter和Facebook）迅速激励着人们不仅使用Internet进行交易，还表达了他们对产品，服务，政策等的看法。情感分析是一个领域研究以提取和分析公众意见。但是，该领域的当前研究主要集中在使用英语构建系统和资源上。这项研究的主要目的是检查有关构建情感词典系统的现有研究，并对非英语数据集进行分类。此外，研究还回顾了用于为非英语语言构建情感词典的工具，从使用机器翻译的工具到基于图的方法。