Search Results for author:
Found 7 papers, 2 papers with code
InstaSynth: Opportunities and Challenges in Generating Synthetic Instagram Data with ChatGPT for Sponsored Content Detection
We investigate the use of LLMs for generating synthetic Instagram captions with two objectives: The first objective (fidelity) is to produce realistic synthetic datasets.
Closing the Loop: Testing ChatGPT to Generate Model Explanations to Improve Human Labelling of Sponsored Content on Social Media
To improve annotation accuracy and, thus, the detection of sponsored content, we propose using chatGPT to augment the annotation process with phrases identified as relevant features and brief explanations.
The Case for a Legal Compliance API for the Enforcement of the EU's Digital Services Act on Social Media Platforms
In the course of under a year, the European Commission has launched some of the most important regulatory proposals to date on platform governance.
Social-Media Activity Forecasting with Exogenous Information Signals
Due to their widespread adoption, social media platforms present an ideal environment for studying and understanding social behavior, especially on information spread.
Malicious and Low Credibility URLs on Twitter during the AstraZeneca COVID-19 Vaccine Development
We investigate the link sharing behavior of Twitter users following the temporary halt of AstraZeneca COVID-19 vaccine development in September 2020.
Social and Information Networks
Cascade-LSTM: Predicting Information Cascades using Deep Neural Networks
Predicting the flow of information in dynamic social environments is relevant to many areas of the contemporary society, from disseminating health care messages to meme tracking.
On the Privacy of dK-Random Graphs
More precisely, we study the boundaries of anonymity based on the structural properties of real graph datasets in terms of how their dK-based anonymized versions resist (or fail) to various types of attacks.
