Papers with advocacy
“#DisabledOnIndianTwitter” : A Dataset towards Understanding the Expression of People with Disabilities on Indian Twitter (2022.findings-aacl)
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| Challenge: | a majority of disabled Indians exist at the margins of society with little to no access to social media . as access to ICTs and high-speed internet grows, Indian Twitter's user base is expanding to include disability influencers, activists, and everyday disabled users. |
| Approach: | They propose a hierarchical annotation taxonomy to classify tweets into various themes including discrimination, advocacy, and self-identification. |
| Outcome: | The proposed taxonomy classifies 2,384 tweets into various themes including discrimination, advocacy, and self-identification. |
Let’s Make Your Request More Persuasive: Modeling Persuasive Strategies via Semi-Supervised Neural Nets on Crowdfunding Platforms (N19-1)
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| Challenge: | Existing models can't quantify persuasiveness of requests or extract successful persuasive strategies. |
| Approach: | They propose a semi-supervised hierarchical neural network model to quantify persuasiveness and identify persuasive strategies in advocacy requests. |
| Outcome: | The proposed method outperforms baseline models and offers increased interpretability of persuasive speech. |
Constructing a Chinese Medical Conversation Corpus Annotated with Conversational Structures and Actions (L18-1)
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| Challenge: | Recent studies have found that patients' advocacy for antibiotic treatment is consequential on antibiotic over-prescribing. |
| Approach: | They propose to analyze a manually transcribed corpus of medical dialogue in Chinese pediatric consultations with annotation of conversational structures and actions. |
| Outcome: | The proposed corpus can shed light on ways to improve physician-patient communication in order to reduce antibiotic over-prescribing. |
HumVI: A Multilingual Dataset for Detecting Violent Incidents Impacting Humanitarian Aid (2024.findings-emnlp)
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Hemank Lamba, Anton Abilov, Ke Zhang, Elizabeth Olson, Henry Dambanemuya, João Bárcia, David Batista, Christina Wille, Aoife Cahill, Joel Tetreault, Alejandro Jaimes
| Challenge: | Humanitarian organizations can analyze data to discover trends, gather aggregated insights, manage security risks, and inform advocacy and funding proposals. |
| Approach: | They present a dataset comprising news articles in three languages containing instances of different types of violent incidents categorized by the humanitarian sector they impact. |
| Outcome: | The proposed framework can be used to identify violent incidents and identify their impact on humanitarian operations. |