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Found 30 papers, 5 papers with code
Twitter Data Augmentation for Monitoring Public Opinion on COVID-19 Intervention Measures
The COVID-19 outbreak is an ongoing worldwide pandemic that was announced as a global health crisis in March 2020.
Detection of Negative Campaign in Israeli Municipal Elections
Our contribution is multi-fold: (1) We provide TONIC—daTaset fOr Negative polItical Campaign in Hebrew—which consists of annotated posts from Facebook related to Israeli municipal elections; (2) We introduce results of a case study, that explored several research questions.
Offensive language detection in Hebrew: can other languages help?
Therefore, automated detection of offensive language is in high demand and it is a serious challenge in multilingual domains.
An Interactive Analysis of User-reported Long COVID Symptoms using Twitter Data
With millions of documented recoveries from COVID-19 worldwide, various long-term sequelae have been observed in a large group of survivors.
Hierarchical summarization of financial reports with RUNNER
This paper reports an approach for summarizing financial texts, which are different from the documents from other domains at least in three parameters: length, structure, and format.
SCE-SUMMARY at the FNS 2020 shared task
This paper reports an approach for summarizing financial texts, which are different from the documents from other domains at least in three parameters: length, structure, and format.
The Financial Narrative Summarisation Shared Task (FNS 2020)
This paper presents the results and findings of the Financial Narrative Summarisation shared task (FNS 2020) on summarising UK annual reports.
Improving Factual Error Correction for Abstractive Summarization via Data Distillation and Conditional-generation Cloze
Improving factual consistency in abstractive summarization has been a focus of current research.
Just ClozE! A Novel Framework for Evaluating the Factual Consistency Faster in Abstractive Summarization
The issue of factual consistency in abstractive summarization has received extensive attention in recent years, and the evaluation of factual consistency between summary and document has become an important and urgent task.
Subjective Bias in Abstractive Summarization
Due to the subjectivity of the summarization, it is a good practice to have more than one gold summary for each training document.
Automated Discovery of Mathematical Definitions in Text with Deep Neural Networks
We also present a new dataset for definition extraction from mathematical texts.
Automated Discovery of Mathematical Definitions in Text
We also present a new dataset for definition extraction from mathematical texts.
Detecting Troll Tweets in a Bilingual Corpus
This paper aims to detect troll tweets in both English and Russian assuming that the tweets are generated by some {``}troll farm.
In Conclusion Not Repetition: Comprehensive Abstractive Summarization With Diversified Attention Based On Determinantal Point Processes
Various Seq2Seq learning models designed for machine translation were applied for abstractive summarization task recently.
HEvAS: Headline Evaluation and Analysis System
We introduce the Headline Evaluation and Analysis System (HEvAS) that performs automatic evaluation of systems in terms of a quality of the generated headlines.
RANLP 2019 Multilingual Headline Generation Task Overview
The task measures the performance of multilingual headline generation systems using the Wikipedia and Wikinews articles in multiple languages.
Query-based summarization using MDL principle
Query-based text summarization is aimed at extracting essential information that answers the query from original text.
MultiLing 2017 Overview
In this brief report we present an overview of the MultiLing 2017 effort and workshop, as implemented within EACL 2017.
Social and linguistic behavior and its correlation to trait empathy
A growing body of research exploits social media behaviors to gauge psychological character-istics, though trait empathy has received little attention.
What's up on Twitter? Catch up with TWIST!
Event detection and analysis with respect to public opinions and sentiments in social media is a broad and well-addressed research topic.
