Automatic text classification is the task of organizing documents into pre-determined classes,
generally using machine learning algorithms. Generally speaking, it is one of the most …

Consumers increasingly rate, review and research products online. Consequently, websites
containing consumer reviews are becoming targets of opinion spam. While recent work has …

Language identification (" LI") is the problem of determining the natural language that a
document or part thereof is written in. Automatic LI has been extensively researched for over …

The coronavirus outbreak has brought unprecedented measures, which forced the
authorities to make decisions related to the instauration of lockdowns in the areas most hit …

Text mining is a new and exciting area of computer science research that tries to solve the
crisis of information overload by combining techniques from data mining, machine learning …

We empirically characterize the performance of discriminative and generative LSTM models
for text classification. We find that although RNN-based generative models are more …

In recent years, online social networking has revolutionized interpersonal communication.
The newer research on language analysis in social media has been increasingly focusing …

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 …

Adequate representation of natural language semantics requires access to vast amounts of
common sense and domain-specific world knowledge. Prior work in the field was based on …

This paper introduces a methodology for determining polarity of text within a multilingual
framework. The method leverages on lexical resources for sentiment analysis available in …