research-article

D-Map+: Interactive Visual Analysis and Exploration of Ego-centric and Event-centric Information Diffusion Patterns in Social Media

Authors:

Zhenhuang Wang,

Xiaoru YuanAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 10, Issue 1

Article No.: 11, Pages 1 - 26

https://doi.org/10.1145/3183347

Published: 28 November 2018 Publication History

Abstract

Information diffusion analysis is important in social media. In this work, we present a coherent ego-centric and event-centric model to investigate diffusion patterns and user behaviors. Applying the model, we propose Diffusion Map+ (D-Maps+), a novel visualization method to support exploration and analysis of user behaviors and diffusion patterns through a map metaphor. For ego-centric analysis, users who participated in reposting (i.e., resending a message initially posted by others) one central user’s posts (i.e., a series of original tweets) are collected. Event-centric analysis focuses on multiple central users discussing a specific event, with all the people participating and reposting messages about it. Social media users are mapped to a hexagonal grid based on their behavior similarities and in the chronological order of repostings. With the additional interactions and linkings, D-Map+ is capable of providing visual profiling of influential users, describing their social behaviors and analyzing the evolution of significant events in social media. A comprehensive visual analysis system is developed to support interactive exploration with D-Map+. We evaluate our work with real-world social media data and find interesting patterns among users and events. We also perform evaluations including user studies and expert feedback to certify the capabilities of our method.

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Sehnan DGoel VMasud SJain CGoyal VChakraborty T(2023)DiVA: A Scalable, Interactive and Customizable Visual Analytics Platform for Information Diffusion on Large NetworksACM Transactions on Knowledge Discovery from Data10.1145/355877117:4(1-33)Online publication date: 24-Feb-2023
https://dl.acm.org/doi/10.1145/3558771
Guo YGuo SJin ZKaul SGotz DCao N(2022)Survey on Visual Analysis of Event Sequence DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.310041328:12(5091-5112)Online publication date: 1-Dec-2022
https://doi.org/10.1109/TVCG.2021.3100413
Wang TLi ZZhang J(2022)Egocentric visual analysis of dynamic citation networkJournal of Visualization10.1007/s12650-022-00862-725:6(1343-1360)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s12650-022-00862-7
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Index Terms

D-Map+: Interactive Visual Analysis and Exploration of Ego-centric and Event-centric Information Diffusion Patterns in Social Media
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Visual analytics

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cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 10, Issue 1

Special Issue on Visual Analytics

January 2019

235 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/3295616

Editor:
Yu Zheng
JD Finance, China

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Copyright © 2018 ACM.

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Publication History

Published: 28 November 2018

Accepted: 01 January 2018

Revised: 01 December 2017

Received: 01 September 2017

Published in TIST Volume 10, Issue 1

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NSFC
German Science Foundation (DFG) in priority research program SPP
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Cited By

Sehnan DGoel VMasud SJain CGoyal VChakraborty T(2023)DiVA: A Scalable, Interactive and Customizable Visual Analytics Platform for Information Diffusion on Large NetworksACM Transactions on Knowledge Discovery from Data10.1145/355877117:4(1-33)Online publication date: 24-Feb-2023
https://dl.acm.org/doi/10.1145/3558771
Guo YGuo SJin ZKaul SGotz DCao N(2022)Survey on Visual Analysis of Event Sequence DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.310041328:12(5091-5112)Online publication date: 1-Dec-2022
https://doi.org/10.1109/TVCG.2021.3100413
Wang TLi ZZhang J(2022)Egocentric visual analysis of dynamic citation networkJournal of Visualization10.1007/s12650-022-00862-725:6(1343-1360)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s12650-022-00862-7
Liu YWu A(2021)POI Recommendation Method Using Deep Learning in Location-Based Social NetworksWireless Communications & Mobile Computing10.1155/2021/91208642021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/9120864
Chen SAndrienko NAndrienko GLi JYuan X(2021)Co-Bridges: Pair-wise Visual Connection and Comparison for Multi-item Data StreamsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.303041127:2(1612-1622)Online publication date: Feb-2021
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Ma XCui KJi CXue P(2020)Visualization of Emergency Needs Posted on Social Media by Metaphor MapData and Information Management10.2478/dim-2020-0021Online publication date: 17-Oct-2020
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Hogräfer MHeitzler MSchulz H(2020)The State of the Art in Map‐Like VisualizationComputer Graphics Forum10.1111/cgf.1403139:3(647-674)Online publication date: 18-Jul-2020
https://doi.org/10.1111/cgf.14031
Subramanian SPushparaj PLiu ZLu A(2019)Explainable Visualization of Collaborative Vandal Behaviors in Wikipedia2019 IEEE Symposium on Visualization for Cyber Security (VizSec)10.1109/VizSec48167.2019.9161504(1-5)Online publication date: Oct-2019
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Chen SLi SChen SYuan X(2019)R-Map: A Map Metaphor for Visualizing Information Reposting Process in Social MediaIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2019.2934263(1-1)Online publication date: 2019
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