| Challenge: | Vaccination corpus is a corpus of texts related to the online vaccination debate . it contains documents from the Internet which reflect different views on vaccinations . |
| Approach: | They present a corpus of texts related to the online vaccination debate annotated with perspectives about attribution, claims and opinions. |
| Outcome: | The Vaccination Corpus contains 294 documents from the Internet which reflect different views on vaccinations. |
Similar Papers
A Multi-layer Annotated Corpus of Argumentative Text: From Argument Schemes to Discourse Relations (L18-1)
Copied to clipboard
| Challenge: | Recent interest in Argumentation Mining has brought to the fore the need for corpora annotated with argument information, which can be used as training data. |
| Approach: | They propose a set of guidelines for the annotation of argument schemes and a new annotation tool for the 'inferential' argument schemes. |
| Outcome: | The proposed corpus includes 112 argumentative microtexts and a new annotation tool. |
Annotating Arguments in a Corpus of Opinion Articles (2022.lrec-1)
Copied to clipboard
Gil Rocha, Luís Trigo, Henrique Lopes Cardoso, Rui Sousa-Silva, Paula Carvalho, Bruno Martins, Miguel Won
| Challenge: | Argument annotation is the process of exposing and justifying one's points of view, with the aim of conveying a logical reasoning through a set of semantically related propositions. |
| Approach: | They propose to use argumentative discourse units to annotate arguments in Portuguese using a multi-layered process to analyze the annotations produced. |
| Outcome: | The proposed model exploits the best practices identified in previous studies while fostering the potential use of the resulting annotated corpus for new purposes. |
Annotating Opinions and Opinion Targets in Student Course Feedback (L18-1)
Copied to clipboard
Janaka Chathuranga, Shanika Ediriweera, Ravindu Hasantha, Pranidhith Munasinghe, Surangika Ranathunga
| Challenge: | a student feedback corpus is a novel resource for opinion target extraction and sentiment analysis. |
| Approach: | They propose to annotate student feedback corpus with an opinion target extraction method and an annotation scheme for sentiment analysis. |
| Outcome: | The proposed corpus summarises student feedback on undergraduate courses . the method is difficult, and the results are presented in a tee . |
A Corpus with Multi-Level Annotations of Patients, Interventions and Outcomes to Support Language Processing for Medical Literature (P18-1)
Copied to clipboard
| Challenge: | In 2015 alone, about 100 manuscripts describing randomized controlled trials for medical interventions were published every day. |
| Approach: | They propose a corpus of 5,000 medical articles annotated with demarcations of text spans that describe the Patient population enrolled, the Interventions studied and to what they were Compared, and the Outcomes measured. |
| Outcome: | The proposed corpus includes 5,000 medical articles describing clinical randomized controlled trials. |
A Corpus for Modeling User and Language Effects in Argumentation on Online Debating (P19-1)
Copied to clipboard
| Challenge: | Existing argumentation datasets have allowed only limited assessment of "user" traits because information on background of users is generally unavailable. |
| Approach: | They present a dataset of 78,376 debates generated over a 10-year period along with surprisingly comprehensive participant profiles. |
| Outcome: | The proposed dataset includes 78,376 debates generated over a 10-year period along with comprehensive participant profiles. |
Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Media (2022.naacl-main)
Copied to clipboard
| Challenge: | Existing approaches to detect vaccine attitudes on social media require abundant annotations and pre-defined aspect categories. |
| Approach: | They propose a semi-supervised approach to detect vaccine attitudes on social media . they use an autoencoding architecture to learn from unlabelled data the topical information of the domain . |
| Outcome: | The proposed model outperforms existing aspect-based models on stance detection and tweet clustering. |
An Environment for Relational Annotation of Political Debates (P19-3)
Copied to clipboard
| Challenge: | Scalable text analysis techniques can open corpora to new questions in computational social sciences and digital humanities. |
| Approach: | They describe a tool that allows annotating newspaper text with rich information about claims (demands) raised by politicians and other actors. |
| Outcome: | The MARDY tool realizes the complete workflow necessary for annotating a large newspaper text collection with rich information about claims (demands) raised by politicians and other actors. |
Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society (2021.findings-emnlp)
Copied to clipboard
Firoj Alam, Shaden Shaar, Fahim Dalvi, Hassan Sajjad, Alex Nikolov, Hamdy Mubarak, Giovanni Da San Martino, Ahmed Abdelali, Nadir Durrani, Kareem Darwish, Abdulaziz Al-Homaid, Wajdi Zaghouani, Tommaso Caselli, Gijs Danoe, Friso Stolk, Britt Bruntink, Preslav Nakov
| Challenge: | a dataset of 16K manually annotated tweets is used to analyze disinformation . the democratic nature of social media has raised questions about the quality and the factuality of the information that is shared on these platforms. |
| Approach: | They use a dataset of manually annotated tweets to analyze COVID-19 disinformation . they show that tweets contain fake cures, rumors, conspiracy theories and xenophobia . |
| Outcome: | The proposed dataset shows that it is useful in monolingual vs. multilingual settings. |
VaccineLies: A Natural Language Resource for Learning to Recognize Misinformation about the COVID-19 and HPV Vaccines (2022.lrec-1)
Copied to clipboard
| Challenge: | VaccineLies can detect misinformation about vaccines on Twitter without using language resources. |
| Approach: | They present a dataset of tweets propagating misinformation about two vaccines . authors propose novel methods to detect misinformation on Twitter and identify stance towards it . |
| Outcome: | VaccineLies can detect misinformation on Twitter and identify the stance towards it. |
Issue Framing in Online Discussion Fora (N19-1)
Copied to clipboard
| Challenge: | In online discussion fora, speakers often make arguments by highlighting certain aspects of the topic. |
| Approach: | They propose to use a newswire and social media annotated corpus to detect issue frames in online discussions. |
| Outcome: | The proposed model can be applied to the domain of discussion fora using multi-task and adversarial training. |