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Found 17 papers, 5 papers with code
Community Needs and Assets: A Computational Analysis of Community Conversations
To facilitate this task, we introduce the first dataset about community needs and assets consisting of 3, 511 conversations from Reddit, annotated using crowdsourced workers.
Infrastructure Ombudsman: Mining Future Failure Concerns from Structural Disaster Response
Current research concentrates on studying discussions on social media related to structural failures to improve disaster response strategies.
Down the Toxicity Rabbit Hole: A Novel Framework to Bias Audit Large Language Models
This paper makes three contributions.
Auditing and Robustifying COVID-19 Misinformation Datasets via Anticontent Sampling
This paper makes two key contributions.
Disentangling Societal Inequality from Model Biases: Gender Inequality in Divorce Court Proceedings
Divorce is the legal dissolution of a marriage by a court.
For Women, Life, Freedom: A Participatory AI-Based Social Web Analysis of a Watershed Moment in Iran's Gender Struggles
In this paper, we present a computational analysis of the Persian language Twitter discourse with the aim to estimate the shift in stance toward gender equality following the death of Mahsa Amini in police custody.
Subjective Crowd Disagreements for Subjective Data: Uncovering Meaningful CrowdOpinion with Population-level Learning
Human-annotated data plays a critical role in the fairness of AI systems, including those that deal with life-altering decisions or moderating human-created web/social media content.
Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive
For (2), we introduce a first-of-its-kind dataset of vicarious offense.
'Beach' to 'Bitch': Inadvertent Unsafe Transcription of Kids' Content on YouTube
Over the last few years, YouTube Kids has emerged as one of the highly competitive alternatives to television for children's entertainment.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Fringe News Networks: Dynamics of US News Viewership following the 2020 Presidential Election
The growing political polarization of the American electorate over the last several decades has been widely studied and documented.
Are Chess Discussions Racist? An Adversarial Hate Speech Data Set
On June 28, 2020, while presenting a chess podcast on Grandmaster Hikaru Nakamura, Antonio Radi\'c's YouTube handle got blocked because it contained "harmful and dangerous" content.
We Don't Speak the Same Language: Interpreting Polarization through Machine Translation
Polarization among US political parties, media and elites is a widely studied topic.
Discovering Bilingual Lexicons in Polyglot Word Embeddings
In this work, we utilize a single Skip-gram model trained on a multilingual corpus yielding polyglot word embeddings, and present a novel finding that a surprisingly simple constrained nearest-neighbor sampling technique in this embedding space can retrieve bilingual lexicons, even in harsh social media data sets predominantly written in English and Romanized Hindi and often exhibiting code switching.
Harnessing Code Switching to Transcend the Linguistic Barrier
Code mixing (or code switching) is a common phenomenon observed in social-media content generated by a linguistically diverse user-base.
Social Media Attributions in the Context of Water Crisis
Attribution of natural disasters/collective misfortune is a widely-studied political science problem.
Voice for the Voiceless: Active Sampling to Detect Comments Supporting the Rohingyas
The Rohingya refugee crisis is one of the biggest humanitarian crises of modern times with more than 600, 000 Rohingyas rendered homeless according to the United Nations High Commissioner for Refugees.
Hope Speech Detection: A Computational Analysis of the Voice of Peace
The recent Pulwama terror attack (February 14, 2019, Pulwama, Kashmir) triggered a chain of escalating events between India and Pakistan adding another episode to their 70-year-old dispute over Kashmir.
