[PDF][PDF] What to do about bad language on the internet
J Eisenstein - Proceedings of the 2013 conference of the North …, 2013 - aclanthology.org
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 …
bad language: text that defies our expectations about vocabulary, spelling, and syntax. This …
Social media in disaster relief: Usage patterns, data mining tools, and current research directions
As social media has become more integrated into peoples' daily lives, its users have begun
turning to it in times of distress. People use Twitter, Facebook, YouTube, and other social …
turning to it in times of distress. People use Twitter, Facebook, YouTube, and other social …
Improved part-of-speech tagging for online conversational text with word clusters
We consider the problem of part-of-speech tagging for informal, online conversational text.
We systematically evaluate the use of large-scale unsupervised word clustering and new …
We systematically evaluate the use of large-scale unsupervised word clustering and new …
Deep learning for pharmacovigilance: recurrent neural network architectures for labeling adverse drug reactions in Twitter posts
Objective Social media is an important pharmacovigilance data source for adverse drug
reaction (ADR) identification. Human review of social media data is infeasible due to data …
reaction (ADR) identification. Human review of social media data is infeasible due to data …
[PDF][PDF] Twitter part-of-speech tagging for all: Overcoming sparse and noisy data
Part-of-speech information is a pre-requisite in many NLP algorithms. However, Twitter text
is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We …
is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We …
[HTML][HTML] Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts
Objective The abundance of text available in social media and health related forums along
with the rich expression of public opinion have recently attracted the interest of the public …
with the rich expression of public opinion have recently attracted the interest of the public …
Context-sensitive twitter sentiment classification using neural network
Sentiment classification on Twitter has attracted increasing research in recent years. Most
existing work focuses on feature engineering according to the tweet content itself. In this …
existing work focuses on feature engineering according to the tweet content itself. In this …
A topic-enhanced word embedding for Twitter sentiment classification
Word representation is crucial to lexical features used in Twitter sentiment analysis models.
Recent work has demonstrated that dense, low-dimensional and real-valued word …
Recent work has demonstrated that dense, low-dimensional and real-valued word …
Rumor detection and classification for twitter data
With the pervasiveness of online media data as a source of information verifying the validity
of this information is becoming even more important yet quite challenging. Rumors spread a …
of this information is becoming even more important yet quite challenging. Rumors spread a …
Online public shaming on Twitter: Detection, analysis, and mitigation
Public shaming in online social networks and related online public forums like Twitter has
been increasing in recent years. These events are known to have a devastating impact on …
been increasing in recent years. These events are known to have a devastating impact on …