Community Shaping in the Digital Age: A Temporal Fusion Framework for Analyzing Discourse Fragmentation in Online Social Networks

• URL: http://arxiv.org/abs/2409.11665v1
• Date: Wed, 18 Sep 2024 03:03:02 GMT
• Title: Community Shaping in the Digital Age: A Temporal Fusion Framework for Analyzing Discourse Fragmentation in Online Social Networks
• Authors: Amirhossein Dezhboro, Jose Emmanuel Ramirez-Marquez, Aleksandra Krstikj,
• Abstract summary: This research presents a framework for analyzing the dynamics of online communities in social media platforms. By combining text classification and dynamic social network analysis, we uncover mechanisms driving community formation and evolution.
• Score: 45.58331196717468
• License: http://creativecommons.org/licenses/by/4.0/
• 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 contributes to echo chamber formation and societal polarization. Our comprehensive approach provides insights into discourse fragmentation, opinion dynamics, and structural aspects of online communities, offering a methodology for understanding the complex interplay between online interactions and societal trends.

Related papers

• Decoding Digital Influence: The Role of Social Media Behavior in Scientific Stratification Through Logistic Attribution Method [6.285608271780605]
  This study comprehensively analyzes the impact of social media on scientific stratification and mobility. It uses an Explainable Logistic Analysis from a meso-level perspective to explore the correlation between social media behaviors and scientific social stratification.
  arXiv  Detail & Related papers  (2024-07-23T02:01:40Z)
• Ethos and Pathos in Online Group Discussions: Corpora for Polarisation Issues in Social Media [6.530320465510631]
  Growing polarisation in society caught the attention of the scientific community as well as news media. We propose to approach the problem by investigating rhetorical strategies employed by individuals in polarising discussions online. We develop multi-topic and multi-platform corpora with manual annotation of appeals to ethos and pathos, two modes of persuasion in Aristotelian rhetoric.
  arXiv  Detail & Related papers  (2024-04-07T09:10:47Z)
• Echo-chambers and Idea Labs: Communication Styles on Twitter [51.13560635563004]
  This paper investigates the communication styles and structures of Twitter (X) communities within the vaccination context. By shedding light on the nuanced nature of communication within social networks, this study emphasizes the significance of understanding the diversity of perspectives within online communities.
  arXiv  Detail & Related papers  (2024-03-28T13:55:51Z)
• From Perils to Possibilities: Understanding how Human (and AI) Biases affect Online Fora [0.12564343689544843]
  Review explores the dynamics of social interactions, user-generated contents, and biases within the context of social media analysis. Three key points of view are: online debates, online support, and human-AI interactions.
  arXiv  Detail & Related papers  (2024-03-21T11:04:41Z)
• EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture [63.85863519876587]
  Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. We propose a new ensemble architecture, EDSA-Ensemble, that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media.
  arXiv  Detail & Related papers  (2023-01-30T11:56:08Z)
• Self-supervised Hypergraph Representation Learning for Sociological Analysis [52.514283292498405]
  We propose a fundamental methodology to support the further fusion of data mining techniques and sociological behavioral criteria. First, we propose an effective hypergraph awareness and a fast line graph construction framework. Second, we propose a novel hypergraph-based neural network to learn social influence flowing from users to users.
  arXiv  Detail & Related papers  (2022-12-22T01:20:29Z)
• Aggression and "hate speech" in communication of media users: analysis of control capabilities [50.591267188664666]
  Authors studied the possibilities of mutual influence of users in new media. They found a high level of aggression and hate speech when discussing an urgent social problem - measures for COVID-19 fighting. Results can be useful for developing media content in a modern digital environment.
  arXiv  Detail & Related papers  (2022-08-25T15:53:32Z)
• Yourfeed: Towards open science and interoperable systems for social media [1.8623205938004257]
  Existing social media platforms make it incredibly difficult for researchers to conduct studies on social media. To close the gap, we introduce Yourfeed, a research tool for conducting ecologically valid social media research.
  arXiv  Detail & Related papers  (2022-07-15T13:49:51Z)
• Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks [90.3475746663728]
  Events are happening in real-world and real-time, which can be planned and organized for occasions, such as social gatherings, festival celebrations, influential meetings or sports activities. Social media platforms generate a lot of real-time text information regarding public events with different topics. However, mining social events is challenging because events typically exhibit heterogeneous texture and metadata are often ambiguous.
  arXiv  Detail & Related papers  (2021-04-02T02:13:10Z)
• The Homophily Principle in Social Network Analysis [13.039459168820901]
  Homophily is the tendency of like-minded people to interact with one another in social groups. The study of homophily can provide eminent insights into the flow of information and behaviors within a society.
  arXiv  Detail & Related papers  (2020-08-21T05:43:59Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.