otherentity ID: covid19

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CHoRaL: Collecting Humor Reaction Labels from Millions of Social Media Users

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractHumor detection has gained attention in recent years due to the desire to understand user-generated content with figurative language. However, substantial individual and cultural differences in humor perception make it …...

31739

German Abusive Language Dataset with Focus on COVID-19

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

The COVID-19 pandemic has had a significant impact on human lives globally. As a result, it is unsurprising that it has influenced hate speech and other sorts of abusive language …...

2

Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

Understanding who blames or supports whom in news text is a critical research question in computational social science. Traditional methods and datasets for sentiment analysis are, however, not suitable for …...

33827

Causal Investigation of Public Opinion during the COVID-19 Pandemic via Social Media Text

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractUnderstanding the needs and fears of citizens, especially during a pandemic such as COVID-19, is essential for any government or legislative entity. An effective COVID-19 strategy further requires that the …...

16599

Towards Readability-Controlled Machine Translation of COVID-19 Texts

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractThis project investigates the capabilities of Machine Translation models for generating translations at varying levels of readability, focusing on texts related to COVID-19. Whilst it is possible to automatically translate …...

3061

Twitter-COMMs: Detecting Climate, COVID, and Military Multimodal Misinformation

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractDetecting out-of-context media, such as “miscaptioned” images on Twitter, is a relevant problem, especially in domains of high public significance. In this work we aim to develop defenses against such …...

21345

Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractRetrieval Augment Generation (RAG) is a recent advancement in Open-Domain Question Answering (ODQA). RAG has only been trained and explored with a Wikipedia-based external knowledge base and is not optimized …...

27035

Medical Concept Mention Identification in Social Media Posts Using a Small Number of Sample References

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractIdentification of mentions of medical concepts in social media text can provide useful information for caseload prediction of diseases like Covid-19 and Measles. We propose a simple model for the …...

20003