Over the last two decades, social media platforms have grown dramatically. Twitter and
Facebook are the two most popular social media platforms, with millions of active users …

Microblogs have recently received widespread interest from NLP researchers. However,
current tools for Japanese word segmentation and POS tagging still perform poorly on …

We propose a transition-based model for joint word segmentation, POS tagging and text
normalization. Different from previous methods, the model can be trained on standard text …

The language used in social media is often characterized by the abundance of informal and
non-standard writing. The normalization of this non-standard language can be crucial to …

We present our work in the normalization of social media texts in Bahasa Indonesia. To
capture the contextual meaning of tokens, we create a neural word embeddings using …

Анализируются возможности четырех программных средств автоматической
коррекции текстов (Яндекс. Спеллер, Afterscan, Bing Spell Check, Texterra) для …

Morphological analysis (MA) and lexical normalization (LN) are both important tasks for
Japanese user-generated text (UGT). To evaluate and compare different MA/LN systems, we …

User generated text in social network sites contains enormous amount and vast variety of
out-of-vocabulary words, formed both deliberately and mistakenly by the end-users. It is of …

State-of-the-art Chinese word segmentation systems typically exploit supervised models
trained on a standard manually-annotated corpus, achieving performances over 95% on a …

Sentiment analysis, or opinion mining, is a computational process to determine the polarity
of a topic, opinion, emotion, or attitude. Most of the work done on sentiment analysis is for …