Software Engineer and Computational Social Science researcher analyzing large-scale social media data to understand online discourse. Uses data science and computational methods to uncover patterns in digital communication and public debate.
Analysis
An analysis of 16,695 Arabic-language tweets about Lebanon finds that posts containing linguistic uncertainty receive approximately 25% higher engagement, particularly in replies.
Paper
A study analyzing 16,695 Arabic-language tweets finds that posts expressing linguistic uncertainty receive significantly higher engagement, particularly replies—an effect described as “uncertainty–reply asymmetry.”
Analysis
This research was originally published on May 10, 2024, and has been republished here following the migration to soufan.tech. In today's fast-paced social media world, TikTok has quickly become a leading platform, particularly in Lebanon, where influencers are shaping trends and significantly impacting the economy. This study,