Community Shaping in the Digital Age: A Temporal Fusion Framework for Analyzing Discourse Fragmentation in Online Social Networks
Amirhossein Dezhboro, Jose Emmanuel Ramirez-Marquez, Aleksandra, Krstikj

TL;DR
This paper introduces a temporal fusion framework combining text and network data to analyze discourse fragmentation and community dynamics in online social networks, validated through a Twitter case study during major U.S. events in 2020.
Contribution
It presents a novel framework integrating social science elements with dynamic social network analysis to understand community formation and discourse fragmentation in social media.
Findings
Discourse fragments include sexism, racism, xenophobia, ableism, homophobia, and religious intolerance.
Rapid cycles of community emergence and dissolution reflect discourse fragmentation.
Real-world events influence discourse dominance and societal polarization.
Abstract
This research presents a framework for analyzing the dynamics of online communities in social media platforms, utilizing a temporal fusion of text and network data. By combining text classification and dynamic social network analysis, we uncover mechanisms driving community formation and evolution, revealing the influence of real-world events. We introduced fourteen key elements based on social science theories to evaluate social media dynamics, validating our framework through a case study of Twitter data during major U.S. events in 2020. Our analysis centers on discrimination discourse, identifying sexism, racism, xenophobia, ableism, homophobia, and religious intolerance as main fragments. Results demonstrate rapid community emergence and dissolution cycles representative of discourse fragments. We reveal how real-world circumstances impact discourse dominance and how social media…
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Taxonomy
TopicsSocial Media and Politics
