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Found 10 papers, 1 papers with code
Demonstrating the Reliability of Self-Annotated Emotion Data
Vent is a specialised iOS/Android social media platform with the stated goal to encourage people to post about their feelings and explicitly label them.
Assessing Social License to Operate from the Public Discourse on Social Media
Our experimental results show that SIRTA is highly effective in distilling stances from social posts for SLO level assessment, and that the continuous monitoring of SLO levels afforded by SIRTA enables the early detection of critical SLO changes.
DAN: Dual-View Representation Learning for Adapting Stance Classifiers to New Domains
We address the issue of having a limited number of annotations for stance classification in a new domain, by adapting out-of-domain classifiers with domain adaptation.
Figurative Usage Detection of Symptom Words to Improve Personal Health Mention Detection
The introduction of figurative usage detection results in an average improvement of 2. 21% F-score of personal health mention detection, in the case of the feature augmentation-based approach.
A Comparison of Word-based and Context-based Representations for Classification Problems in Health Informatics
Distributed representations of text can be used as features when training a statistical classifier.
Recognising Agreement and Disagreement between Stances with Reason Comparing Networks
We identify agreement and disagreement between utterances that express stances towards a topic of discussion.
Does Multi-Task Learning Always Help?: An Evaluation on Health Informatics
Multi-Task Learning (MTL) has been an attractive approach to deal with limited labeled datasets or leverage related tasks, for a variety of NLP problems.
Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspective
Epidemic intelligence deals with the detection of disease outbreaks using formal (such as hospital records) and informal sources (such as user-generated text on the web) of information.
Shot Or Not: Comparison of NLP Approaches for Vaccination Behaviour Detection
Vaccination behaviour detection deals with predicting whether or not a person received/was about to receive a vaccine.
Cross-Target Stance Classification with Self-Attention Networks
In stance classification, the target on which the stance is made defines the boundary of the task, and a classifier is usually trained for prediction on the same target.
