[HTML][HTML] Capturing the patient's perspective: a review of advances in natural language processing of health-related text
Background: Natural Language Processing (NLP) methods are increasingly being utilized to
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
BERTweet: A pre-trained language model for English Tweets
We present BERTweet, the first public large-scale pre-trained language model for English
Tweets. Our BERTweet, having the same architecture as BERT-base (Devlin et al., 2019), is …
Tweets. Our BERTweet, having the same architecture as BERT-base (Devlin et al., 2019), is …
When a disaster happens, we are ready: Location mention recognition from crisis tweets
Geolocation information is important for humanitarian organizations to gain situational
awareness and deliver timely aid during disasters. Towards addressing the problem of …
awareness and deliver timely aid during disasters. Towards addressing the problem of …
Improving lda topic models for microblogs via tweet pooling and automatic labeling
Twitter, or the world of 140 characters poses serious challenges to the efficacy of topic
models on short, messy text. While topic models such as Latent Dirichlet Allocation (LDA) …
models on short, messy text. While topic models such as Latent Dirichlet Allocation (LDA) …
Social media mining for toxicovigilance: automatic monitoring of prescription medication abuse from Twitter
Introduction Prescription medication overdose is the fastest growing drug-related problem in
the USA. The growing nature of this problem necessitates the implementation of improved …
the USA. The growing nature of this problem necessitates the implementation of improved …
[PDF][PDF] Shared tasks of the 2015 workshop on noisy user-generated text: Twitter lexical normalization and named entity recognition
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 …
text normalization task with 10 participants; and (2) a named entity tagging task with 8 …
Detecting sentiment dynamics and clusters of Twitter users for trending topics in COVID-19 pandemic
COVID-19 caused a significant public health crisis worldwide and triggered some other
issues such as economic crisis, job cuts, mental anxiety, etc. This pandemic plies across the …
issues such as economic crisis, job cuts, mental anxiety, etc. This pandemic plies across the …
Natural language processing, sentiment analysis, and clinical analytics
A Rajput - Innovation in health informatics, 2020 - Elsevier
Abstract Recent advances in Big Data have prompted healthcare practitioners to utilize the
data available on social media to discern sentiment and emotions' expression. Health …
data available on social media to discern sentiment and emotions' expression. Health …
Colloquial indonesian lexicon
NA Salsabila, YA Winatmoko… - … Conference on Asian …, 2018 - ieeexplore.ieee.org
Colloquial Indonesian Lexicon Page 1 Colloquial Indonesian Lexicon Nikmatun Aliyah
Salsabila∗‡, Yosef Ardhito Winatmoko† Ali Akbar Septiandri∗, Ade Jamal∗ ∗Faculty of …
Salsabila∗‡, Yosef Ardhito Winatmoko† Ali Akbar Septiandri∗, Ade Jamal∗ ∗Faculty of …
Machine learning and natural language processing for geolocation-centric monitoring and characterization of opioid-related social media chatter
Importance Automatic curation of consumer-generated, opioid-related social media big data
may enable real-time monitoring of the opioid epidemic in the United States. Objective To …
may enable real-time monitoring of the opioid epidemic in the United States. Objective To …