Investigating the Effect of Emoji in Opinion Classification of Uzbek Movie Review Comments

Opinion mining on social media posts has become more and more popular. Users often express their opinion on a topic not only with words but they also use image symbols such as emoticons and emoji. In this paper, we investigate the effect of emoji-based features in opinion classification of Uzbek texts, and more specifically movie review comments from YouTube. Several classification algorithms are tested, and feature ranking is performed to evaluate the discriminative ability of the emoji-based features.Comment: 10 pages, 1 figure, 3 table

Publishing and syndication information across the education's sites using the RSS feed

With the increasing number of demand for access to education, we need the new technologies to facilitate learning. The good opportunity is to use the Web, which is an enormous and unlimited source of useful and varied kinds of information. Online learning and teaching is becoming more and more popular. Besides the teaching and learning techniques the education environments also consists a communication tool which allows easy publications and syndications the information (news) across the different education Web sites. This paper presents some statistics related to news syndication and the data format used by publishers for news publication. We describe two of the most popular formats currently used to publish and retrieve news information; the HTML non-structured data format and the XML-based RSS-feed format

Investigating the Effect of Emoji in Opinion Classification of Uzbek Movie Review Comments

Opinion mining on social media posts has become more and more popular. Users often express their opinion on a topic not only with words but they also use image symbols such as emoticons and emoji. In this paper, we investigate the effect of emoji-based features in opinion classification of Uzbek texts, and more specifically movie review comments from YouTube. Several classification algorithms are tested, and feature ranking is performed to evaluate the discriminative ability of the emoji-based features