This article presents a discussion on the main linguistic phenomena which cause difficulties
in the analysis of user-generated texts found on the web and in social media, and proposes …

It is not always easy to keep track of what tools are currently available for a particular
annotation task, nor is it obvious how the provided models will perform on a given data set …

Named entity recognition (NER) constitutes an important step in the processing of
unstructured text content for the extraction of information as well as for the computer …

The paper presents a discussion on the main linguistic phenomena of user-generated texts
found in web and social media, and proposes a set of annotation guidelines for their …

The present German political speeches corpus follows from a initial release which has been
used in various research contexts. This article documents an updated and extended version …

Emojis have become ubiquitous in digital communication, due to their visual appeal as well
as their ability to vividly convey human emotion, among other factors. The growing …

This paper presents the German Twitter section of a large (2 billion word) bilingual Social
Media corpus for Hate Speech research, discussing the compilation, pseudonymization and …

Part of speech tagging is a process that seeks to identify the grammatical classes of words
and symbols (tokens) in a sentence. For Brazilian Portuguese, there is a variety of …

In this work, we present a model for building type classification from Twitter text messages
(tweets) by employing geo-spatial textmining methods. First, we apply standard text pre …

GeRedE is a 270 million token German CMC corpus containing approximately 380,000
submissions and 6,800,000 comments posted on Reddit between 2010 and 2018. Reddit is …