Introduction

The proposed methodology offer the possibility to the reader to express, in a binary form, his feeling toward articles, texts, blog posts available on the web. The suggested sentiment can be chosen from a limited classification and associated with the text using intelligent data analysis techniques based on sentiment text analysis.

Technical features

The proposed methodology offer the possibility to the reader to express, in a binary form, his feeling toward articles, texts, blog posts available on the web. Sentiment expression is not yet widely adopted in lieu of liking because the typical GUI means employed to deploy it are not simple enough on the user; in order to overcome this limitation we propose a novel method of display sentiment expression boxes under a blog post or news piece, that combines intelligent data analysis and widely used GUI elements. The innovative part of our method consists of lowering further the cognitive load by showing only the statistically appropriate feeling, a choice dependent on intelligent data analysis algorithms, bringing it down to a level quite similar to the one enticed by the process of liking. In this way the user is more attracted by the idea of sentiment expression, and more data can be gathered in order to better distribute the text on a website.

Possible Applications

• Blogging systems;
• CMSs;
• Sentiment Expression on social Networks and Ecommerce sites.

Advantages

• Computational easiness;
• Highly customisable;
• Interfaceable with common CMSs and blogging systems.