Prestigious ACM journal publishes study by IMFD researchers on frame identification in social networks

A recent study entitled "Unsupervised Framing Analysis for Social Media Discourse in Polarizing Events," by researchers IMFD Hernán Sarmiento (IMFD Innovation), Jorge Ortiz (DCC UCH), Felipe Bravo-Márquez (DCC UCH), and Sebastián Valenzuela (PUC), together with Marcelo Santos (UDP) and Ricardo Córdova, was published in the prestigious journal ACM Transactions on the Web (TWEB), published by the Association for Computing Machinery. The research examines how "frames" emerge in polarized online conversations, with a particular focus on social media platforms. These frames, complex and subtle concepts that shape discussions, play a key role in how users group together and communicate about controversial issues. 

The study proposesproposes an unsupervised methodology to identify and characterize these frames, using machine learning techniques , network analysis, and natural language processing (NLP). In order to rigorously evaluate the frames identified, the study proposes the introduction of new metrics to understand the topics arising from polarizing conversations, referred to as homogeneity and relevance.  

To validate this proposal, a case study on the 2021 Chilean presidential elections is presented, using data extracted from Twitter (X) and WhatsApp. 

"This real-life case allows us to observe how frames change in response to specific events and the particular characteristics of each platform," explains Hernán Sarmiento, IMFD Innovation Engineer. The study provides new tools and insights into how frames influence online polarization, laying the groundwork for future research on the dynamics of digital communities, especially those involved in highly polarized events.

You can find more details at the link: https://dl.acm.org/doi/10.1145/3711912

Graphical demonstration of the study