The studying of opinion dynamics and its propagation within social networks is crucial for addressing a wide range of challenges, including political polarization, public health, and marketing strateg...
The paper proposes a Friedkin‑Johnsen based framework to identify influential users in online social networks and assess how they shape community opinion. By manipulating initial opinions in experiments, the authors show that top influencers can significantly shift overall community sentiment, and their influence extends beyond direct neighbors to second‑degree contacts. The framework is validated on a tweet dataset from the U.S. presidential election, illustrating the power of digital influencers to alter public opinion.
By Omran Berjawi, Rida Khatoun, Giuseppe Fenza
OpenAI banned likely China-origin accounts using AI to generate English social posts and Spanish-language articles.
The paper reviews how large language models (LLMs) are being used to model social networks, highlighting their ability to represent users, relationships, and interactions through natural language. It categorizes existing work into network generative models—split into selection‑based and interaction‑based approaches—and dynamic process models, which cover opinion dynamics, information diffusion, and rumor propagation. The survey also discusses the advantages of LLMs for realistic, context‑aware social behavior, while noting limitations such as social biases and prompt sensitivity, and outlines open research challenges and future directions.
By Shikha Mallick, Alex Thomo, Akrati Saxena
The paper presents a method for automatically distinguishing scientists from non‑scientists on X/Twitter using user biographies and tweets. It reports classification performance up to an F1 score of 0.88 with Random Forests and 0.96 with a contrastively fine‑tuned DeBERTa model in an ensemble. Additionally, the authors release two labeled datasets of X users and their content for further research.
By Philipp Meier, Katarina Boland, Laura Kallmeyer, Stefan Dietze
arXiv:2608. 05259v1 Announce Type: cross Abstract: Online social networks increasingly expose people to users who propagate discriminatory, hateful, and violent content.
By Francesco Benedetti, Antonio Pellicani, Gianvito Pio, Michelangelo Ceci