Opinion mining (OM) of Internet reviews is one of the key issues in text analysis. As the rapid growth of the Internet reviews, users pay more attention to all this fine-grained information when browsing comments. Therefore, aspect-level OM can help consumers make better decisions. In last decade, researchers conducted opinion extraction and analysis on a large number of Internet reviews corpus, and have achieved fruitful research results and broaden the scope of application. There were also some scholars conducted summaries on the present situation of OM methods. To rectify the lack of specific summaries on aspect extraction and opinion expression extraction, this paper analyzes and summarizes the recent research status of aspect-level OM on Internet reviews. The paper describes the aspect-level OM, introduces the different methods of aspect extraction and opinion expression extraction, and summarizes the evaluation measures of aspect-level OM and application values. In the end, it provides an overview of the future challenges along with a synopsis on the existing techniques. This specific survey on aspect-level OM helps to evaluate the different methods and find valuable research direction.