KAUST encouraged attendees of the 2015 Winter Enrichment Program (WEP) to share their experiences on social media using the hashtag #wep2015. The university provided tips for participants to effectively use platforms like Facebook, Twitter, and Instagram during the event. KAUST emphasized responsible sharing and respect for the university's multicultural community when posting. Why it matters: This initiative aimed to amplify the reach of WEP's activities and engage a broader audience in KAUST's community and knowledge-sharing efforts.
A new mini-batch strategy using aggregated relational data is proposed to fit the mixed membership stochastic blockmodel (MMSB) to large networks. The method uses nodal information and stochastic gradients of bipartite graphs for scalable inference. The approach was applied to a citation network with over two million nodes and 25 million edges, capturing explainable structure. Why it matters: This research enables more efficient community detection in massive networks, which is crucial for analyzing complex relationships in various domains, but this article has no clear connection to the Middle East.
Fudan University's Zhongyu Wei presented research on social simulation driven by LLMs, covering individual and large-scale social movement simulation. Wei directs the Data Intelligence and Social Computing Lab (Fudan DISC) and has published extensively on multimodal large models and social computing. His work includes the Volcano multimodal model, DISC-MedLLM, and ElectionSim. Why it matters: Using LLMs for social simulation could provide new tools for understanding and potentially predicting social dynamics in the Arab world.