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Found 13 papers, 6 papers with code
Uncovering Latent Arguments in Social Media Messaging by Employing LLMs-in-the-Loop Strategy
The widespread use of social media has led to a surge in popularity for automated methods of analyzing public opinion.
Uncovering Latent Themes of Messaging on Social Media by Integrating LLMs: A Case Study on Climate Campaigns
Furthermore, this method efficiently maps the text and the newly discovered themes, enhancing our understanding of the thematic nuances in social media messaging.
Interactive Concept Learning for Uncovering Latent Themes in Large Text Collections
Experts across diverse disciplines are often interested in making sense of large text collections.
Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging
Climate change is the defining issue of our time, and we are at a defining moment.
Weakly Supervised Learning for Analyzing Political Campaigns on Facebook
Social media platforms are currently the main channel for political messaging, allowing politicians to target specific demographics and adapt based on their reactions.
Understanding COVID-19 Vaccine Campaign on Facebook using Minimal Supervision
In the age of social media, where billions of internet users share information and opinions, the negative impact of pandemics is not limited to the physical world.
A Holistic Framework for Analyzing the COVID-19 Vaccine Debate
The Covid-19 pandemic has led to infodemic of low quality information leading to poor health decisions.
Twitter User Representation Using Weakly Supervised Graph Embedding
Social media platforms provide convenient means for users to participate in multiple online activities on various contents and create fast widespread interactions.
Analysis of Twitter Users' Lifestyle Choices using Joint Embedding Model
Multiview representation learning of data can help construct coherent and contextualized users' representations on social media.
Do You Do Yoga? Understanding Twitter Users' Types and Motivations using Social and Textual Information
Leveraging social media data to understand people's lifestyle choices is an exciting domain to explore but requires a multiview formulation of the data.
Does Yoga Make You Happy? Analyzing Twitter User Happiness using Textual and Temporal Information
Although yoga is a multi-component practice to hone the body and mind and be known to reduce anxiety and depression, there is still a gap in understanding people's emotional state related to yoga in social media.
Yoga-Veganism: Correlation Mining of Twitter Health Data
We need to mine the data to explore hidden patterns or unknown correlations, find out the dominant topic in data and understand people's interest through the discussions.
Ex-Twit: Explainable Twitter Mining on Health Data
Since most machine learning models provide no explanations for the predictions, their predictions are obscure for the human.
