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Found 17 papers, 4 papers with code
Improving User Behavior Prediction: Leveraging Annotator Metadata in Supervised Machine Learning Models
Supervised machine-learning models often underperform in predicting user behaviors from conversational text, hindered by poor crowdsourced label quality and low NLP task accuracy.
Crowdsource, Crawl, or Generate? Creating SEA-VL, a Multicultural Vision-Language Dataset for Southeast Asia
Beyond crowdsourcing, our initiative goes one step further in the exploration of the automatic collection of culturally relevant images through crawling and image generation.
What is a Social Media Bot? A Global Comparison of Bot and Human Characteristics
Chatter on social media is 20% bots and 80% humans.
What talking you?: Translating Code-Mixed Messaging Texts to English
We also release our dataset in this link https://github. com/luoqichan/singlish.
$\textit{Who Speaks Matters}$: Analysing the Influence of the Speaker's Ethnicity on Hate Classification
We find that the presence of implicit dialect markers in inputs causes model outputs to flip more than the presence of explicit markers.
Limpeh ga li gong: Challenges in Singlish Annotations
Singlish, or Colloquial Singapore English, is a language formed from oral and social communication within multicultural Singapore.
Disentangling Singlish Discourse Particles with Task-Driven Representation
Singlish, or formally Colloquial Singapore English, is an English-based creole language originating from the SouthEast Asian country Singapore.
Examining the Influence of Political Bias on Large Language Model Performance in Stance Classification
In this study, we investigate the political biases of LLMs within the stance classification task, specifically examining whether these models exhibit a tendency to more accurately classify politically-charged stances.
DIVERSE: A Dataset of YouTube Video Comment Stances with a Data Programming Model
However, there is a notable lack of data for analyzing opinions on military recruiting efforts online, compounded by challenges in stance labeling, which is crucial for understanding public perceptions.
Reverse Projection: Real-Time Local Space Texture Mapping
We present Reverse Projection, a novel projective texture mapping technique for painting a decal directly to the texture of a 3D object.
Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classification
In general, we discover that LLMs do not routinely outperform their smaller supervised machine learning models, and thus call for stance detection to be a benchmark for which LLMs also optimize for.
How Hate Speech Varies by Target Identity: A Computational Analysis
We also find that words associated with hate speech targeting specific identities often relate to stereotypes, histories of oppression, current social movements, and other social contexts specific to identities.
Using Graph-Aware Reinforcement Learning to Identify Winning Strategies in Diplomacy Games (Student Abstract)
We developed a two-tier approach that first encodes sociolinguistic behavior as linguistic features then use reinforcement learning to estimate the advantage afforded to any player.
Will You Dance To The Challenge? Predicting User Participation of TikTok Challenges
This paper investigates social contagion of TikTok challenges through predicting a user's participation.
Coordinating Narratives and the Capitol Riots on Parler
Coordinated disinformation campaigns are used to influence social media users, potentially leading to offline violence.
The Coronavirus is a Bioweapon: Analysing Coronavirus Fact-Checked Stories
The 2020 coronavirus pandemic has heightened the need to flag coronavirus-related misinformation, and fact-checking groups have taken to verifying misinformation on the Internet.
KOSMOS: Knowledge-graph Oriented Social media and Mainstream media Overview System
We introduce KOSMOS, a knowledge retrieval system based on the constructed knowledge graph of social media and mainstream media documents.
