Improvements of Webometrics by Using Sentiment Analysis for Better Accessibility of the Web
The paper discusses the webometric model for effective acquirement of relevant information from the web that would better separate the useful data from the useless. Our research emphasis has been placed on techniques that would better reflect the semantic content of single pages. Webometrics is purely a quantitative approach to the web, which can be enhanced by qualitative methods and thereby allows us to expand the possibilities of a study problem. Sentiment analysis may be used as a qualitative complement to quantitative approach. This analysis provides a technique of sophisticated analysis of sentences using mathematical and statistical methods and linguistic analysis of text. Extension of the webometric techniques of sentiment analysis methods leads up to a better machine understanding of a web page and its overall semantic meaning. It can be assumed that the designed model will reduce the irrelevant web search results and thereby facilitate user access to the information on the web. The introductory part of the paper explains the concept of the sentiment analysis and the basic functional background of the webometric techniques.