1164 hits

With the ever increasing of internet applications and social networking sites, people nowadays can easily express their feelings towards any products and services. These online reviews act as an important source for further analysis and improved decision making. These reviews are mostly unstructured by nature and thus, need processing like sentiment analysis and classification to provide a meaningful information for future uses. In text analysis tasks, the appropriate selection of words/features will have a huge impact on the effectiveness of the classifier. Thus, this paper explores the effect of the pre-processing strategies in the sentiment analysis of online movie reviews. In this paper, supervised machine learning method was used to classify the reviews. The support vector machine (SVM) with linear and non-linear kernel has been considered as classifier for the classification of the reviews. The performance of the classifier is critically examined based on the results of precision.....

590 hits

Analysing students_ feedback and their expressed emotions toward any subjects could help lecturers to understand their students_ learning behaviour. Several platforms are used by students to express their feelings such as through social networking sites, blogs, discussion forums and the university survey systems. However, the feedbacks typically contain thousands of sentences and are from various sources which makes analysing them a cumbersome and tedious work. In this regard, sentiment analysis (SA) has been proposed to automate the process of mining user feedback into valuable information. This paper discusses the principles of SA, its potential benefits, and its application in the educational field based on the synthesis of previous studies. We suggest that SA can help lecturers to easily understand the needs and problems of their students. In particular, a framework and a performance evaluation method were proposed to help guide the implementation of the SA in the education domain......

6 hits