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Found 14 papers, 4 papers with code
Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse
Online abuse and offensive language on social media have become widespread problems in today’s digital age.
TEASER: Towards Efficient Aspect-based SEntiment Analysis and Recognition
Prior works formulate this as a sequence tagging problem or solve this task using a span-based extract-then-classify framework where first all the opinion targets are extracted from the sentence, and then with the help of span representations, the targets are classified as positive, negative, or neutral.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
Towards Sentiment Analysis of Tobacco Products’ Usage in Social Media
We release SentiSmoke-Twitter and SentiSmoke-Reddit datasets, along with a comprehensive annotation schema for identifying tobacco products’ sentiment.
Incorporating Subjectivity into Gendered Ambiguous Pronoun (GAP) Resolution using Style Transfer
The GAP dataset is a Wikipedia-based evaluation dataset for gender bias detection in coreference resolution, containing mostly objective sentences.
Towards Fine-grained Classification of Climate Change related Social Media Text
We benchmark both the datasets for climate change stance detection and fine-grained classification using state-of-the-art methods in text classification.
Text Simplification for Comprehension-based Question-Answering
Text simplification is the process of splitting and rephrasing a sentence to a sequence of sentences making it easier to read and understand while preserving the content and approximating the original meaning.
Team Rouges at SemEval-2020 Task 12: Cross-lingual Inductive Transfer to Detect Offensive Language
We show that our model performs competitively on all five languages, obtaining the fourth position in the English task with an F1-score of 0. 919 and eighth position in the Turkish task with an F1-score of 0. 781.
Towards Code-switched Classification Exploiting Constituent Language Resources
This conversion allows us to utilize the higher resource availability for its constituent languages for multiple downstream tasks.
Cross-lingual Inductive Transfer to Detect Offensive Language
We show that our model performs competitively on all five languages, obtaining the fourth position in the English task with an F1-score of $0. 919$ and eighth position in the Turkish task with an F1-score of $0. 781$.
Sarcasm Detection using Context Separators in Online Discourse
We show that our proposed architecture performs competitively for both the datasets.
Ranked #1 on
Sarcasm Detection
on FigLang 2020 Twitter Dataset
BERT-based Ensembles for Modeling Disclosure and Support in Conversational Social Media Text
There is a growing interest in understanding how humans initiate and hold conversations.
Ranked #1 on
Text Classification
on AffCon 2020 Emotion Detection
SentiInc: Incorporating Sentiment Information into Sentiment Transfer Without Parallel Data
We address this issue by providing a simple framework for encoding sentiment-specific information in the target sentence while preserving the content information.
Ranked #1 on
Text Style Transfer
on Yelp Review Dataset (Large)
Towards Detection of Subjective Bias using Contextualized Word Embeddings
Subjective bias detection is critical for applications like propaganda detection, content recommendation, sentiment analysis, and bias neutralization.
Ranked #1 on
Bias Detection
on Wiki Neutrality Corpus
SmokEng: Towards Fine-grained Classification of Tobacco-related Social Media Text
Contemporary datasets on tobacco consumption focus on one of two topics, either public health mentions and disease surveillance, or sentiment analysis on topical tobacco products and services.
