Search Results for author:
Found 16 papers, 4 papers with code
On the Usefulness of Personality Traits in Opinion-oriented Tasks
We use a deep bidirectional transformer to extract the Myers-Briggs personality type from user-generated data in a multi-label and multi-class classification setting.
Improving Evidence Retrieval with Claim-Evidence Entailment
Claim verification is challenging because it requires first to find textual evidence and then apply claim-evidence entailment to verify a claim.
COIN – an Inexpensive and Strong Baseline for Predicting Out of Vocabulary Word Embeddings
Word embedding models only include terms that occur a sufficient number of times in their training corpora.
DMDD: A Large-Scale Dataset for Dataset Mentions Detection
We use DMDD to establish baseline performance for dataset mention detection and linking.
Opinion Prediction with User Fingerprinting
Experimental results show novel insights that were previously unknown such as better predictions for an increase in dynamic history length, the impact of the nature of the article on performance, thereby laying the foundation for further research.
Stay on Topic, Please: Aligning User Comments to the Content of a News Article
We proposed a BERTAC, BAERT-based approach that learn jointly article-comment embeddings and infers the relevance class of comments.
Predicting Personal Opinion on Future Events with Fingerprints
We evaluate the proposed model on this dataset.
Cannot Predict Comment Volume of a News Article before (a few) Users Read It
We show that the early arrival rate of comments is the best indicator of the eventual number of comments.
Birds of a Feather Flock Together: Satirical News Detection via Language Model Differentiation
In this work, we propose a method that differentiates the satirical news and true news.
Stance Prediction for Contemporary Issues: Data and Experiments
We investigate whether pre-trained bidirectional transformers with sentiment and emotion information improve stance detection in long discussions of contemporary issues.
Regular Expression Guided Entity Mention Mining from Noisy Web Data
Finally, a human expert is asked to label a small set of documents and the neural network is fine tuned on those documents.
DebugSL: An Interactive Tool for Debugging Sentiment Lexicons
We introduce DebugSL, a visual (Web) debugging tool for sentiment lexicons (SLs).
Satirical News Detection and Analysis using Attention Mechanism and Linguistic Features
Satirical news is considered to be entertainment, but it is potentially deceptive and harmful.
