Sentiments or opinions from social media provide the most up-to-date and inclusive
information, due to the proliferation of social media and the low barrier for posting the …

The aim of this study is to provide an overview the state-of-the-art elements of text
classification. For this purpose, we first select and investigate the primary and recent studies …

The new transformed read-write Web has resulted in a rapid growth of user generated
content on the Web resulting into a huge volume of unstructured data. A substantial part of …

Online reviews are becoming increasingly important for decision-making. Consumers often
refer to online reviews for opinions before making a purchase. Marketers also acknowledge …

We employ multiple heterogeneous data sources, including historical transaction data,
technical indicators, stock posts, news and Baidu index, to predict the directions of stock …

Over the last two decades and with the widespread use of social media and e-commerce
sites, scientific research in the field of sentiment analysis (SA) has made considerable …

Commonly, product review analysis includes extracting sentiment from product documents.
The contextual aspect contained in a review document has potential to improve results …

The accuracy of a text classification method based on a SVM learner depends on the
weighting metric used in order to assign a weight to a term. Weighting metrics can be …

The effective representation of the relationship between the documents and their contents is
crucial to increase classification performance of text documents in the text classification …

Discussion features in online communities can be effectively used to diagnose depression
and allow other users or experts to provide self-help resources to those in need. Automatic …