This paper deals with automatic two class document-level sentiment classification. We
retrieved textual documents with political, business, economic and financial content from five …

In this paper, sentiment classification techniques are incorporated into the domain of political
news from columns in different Turkish news sites. We compared four supervised machine …

The aim of this paper is to experiment with different machine learning approaches to
predict/classify the sentiment on various available sentiment corpuses named as Subjectivity …

In this article, we explore the task of sentiment analysis for Ukrainian and Russian news,
analyze different approaches and linguistics resources for sentiment analysis. We …

Document-level sentiment classification aims to automate the task of classifying a textual
review, which is given on a single topic, as expressing a positive or negative sentiment. In …

Opinions have always influenced our behaviours and they have a key role in human
activities. Nowadays, online opinion resources such as newspapers, blogs, and reviews …

Sentiment classification of text is one of the major tasks of natural language processing
which has has gained significant interest recently. While there are many researches in this …

Sentiment classification of texts written in Serbian is still an under-researched topic. One of
the open issues is how the different forms of morphological normalization affect the …

We have explored different methods of improving the accuracy of a Naive Bayes classifier
for sentiment analysis. We observed that a combination of methods like effective negation …

In news domain, sentiments captured in the form of sentiment labels (emoticon) give a quick
feedback of reactions towards the contents of the news. As these reactions are valuable …