The rise of social media has brought computational linguistics in ever-closer contact with
bad language: text that defies our expectations about vocabulary, spelling, and syntax. This …

This paper presents the results of the two shared tasks associated with W-NUT 2015:(1) a
text normalization task with 10 participants; and (2) a named entity tagging task with 8 …

Abstract Machine learning, including neural network techniques, have been applied to
virtually every domain in natural language processing. One problem that has been …

Twitter provides access to large volumes of data in real time, but is notoriously noisy,
hampering its utility for NLP. In this article, we target out-of-vocabulary words in short text …

Microblog normalisation methods often utilise complex models and struggle to differentiate
between correctly-spelled unknown words and lexical variants of known words. In this …

As social media continue to grow, the zeitgeist of society is increasingly found not in the
headlines of traditional media institutions, but in the activity of ordinary individuals. The …

This paper presents a challenge to the community: given a large corpus of written text
aligned to its normalized spoken form, train an RNN to learn the correct normalization …

Social media language contains huge amount and wide variety of nonstandard tokens,
created both intentionally and unintentionally by the users. It is of crucial importance to …

Computational syntactic processing is a fundamental technique in natural language
processing. It normally serves as a pre-processing method to transform natural language …

The proliferation of Web 2.0 technologies and the increasing use of computer-mediated
communication resulted in a new form of written text, termed microtext. This poses new …