research-article

Different approaches to community evolution prediction in blogosphere

Authors:

Stanisław Saganowski,

Przemysław Kazienko,

Jarosław KoźlakAuthors Info & Claims

ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

Pages 1291 - 1298

https://doi.org/10.1145/2492517.2500231

Published: 25 August 2013 Publication History

Abstract

Predicting the future direction of community evolution is a problem with high theoretical and practical significance. It allows to determine which characteristics describing communities have importance from the point of view of their future behaviour. Knowledge about the probable future career of the community aids in the decision concerning investing in contact with members of a given community and carrying out actions to achieve a key position in it. It also allows to determine effective ways of forming opinions or to protect group participants against such activities. In the paper, a new approach to group identification and prediction of future events is presented together with the comparison to existing method. Performed experiments prove a high quality of prediction results. Comparison to previous studies shows that using many measures to describe the group profile, and in consequence as a classifier input, can improve predictions.

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Cited By

Chen JZhao HYang XLiu MYu ZLiu M(2022)Community Evolution Prediction Based on Multivariate Feature Sets and Potential Structural FeaturesMathematics10.3390/math1020380210:20(3802)Online publication date: 15-Oct-2022
https://doi.org/10.3390/math10203802
Wang ZXu QLi W(2022)Multi-Layer Feature Fusion-Based Community Evolution PredictionFuture Internet10.3390/fi1404011314:4(113)Online publication date: 6-Apr-2022
https://doi.org/10.3390/fi14040113
Khafaei TTavakoli Taraghi AHosseinzadeh MRezaee A(2022)The Sensitivity of Community Extra-Structural Features on Event Prediction in Dynamic Social NetworksSocial Science Computer Review10.1177/0894439321105581341:4(1187-1206)Online publication date: 27-Feb-2022
https://doi.org/10.1177/08944393211055813
Show More Cited By

Index Terms

Different approaches to community evolution prediction in blogosphere
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms
      1. Web-based interaction
2. Information systems
  1. Information retrieval
    1. Document representation
  2. Information systems applications
    1. Data mining

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cover image ACM Conferences

ASONAM '13: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

August 2013

1558 pages

ISBN:9781450322409

DOI:10.1145/2492517

General Chairs:
Jon Rokne
University of Calgary, Calgary, AB, Canada
,
Christos Faloutsos
Carnegie Mellon University, Pittsburgh, PA

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 August 2013

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ASONAM '13: Advances in Social Networks Analysis and Mining 2013

August 25 - 28, 2013

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Cited By

Chen JZhao HYang XLiu MYu ZLiu M(2022)Community Evolution Prediction Based on Multivariate Feature Sets and Potential Structural FeaturesMathematics10.3390/math1020380210:20(3802)Online publication date: 15-Oct-2022
https://doi.org/10.3390/math10203802
Wang ZXu QLi W(2022)Multi-Layer Feature Fusion-Based Community Evolution PredictionFuture Internet10.3390/fi1404011314:4(113)Online publication date: 6-Apr-2022
https://doi.org/10.3390/fi14040113
Khafaei TTavakoli Taraghi AHosseinzadeh MRezaee A(2022)The Sensitivity of Community Extra-Structural Features on Event Prediction in Dynamic Social NetworksSocial Science Computer Review10.1177/0894439321105581341:4(1187-1206)Online publication date: 27-Feb-2022
https://doi.org/10.1177/08944393211055813
Karatas ASahin S(2022)A Novel Efficient Method for Tracking Evolution of Communities in Dynamic NetworksIEEE Access10.1109/ACCESS.2022.317047610(46276-46290)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3170476
Kadkhoda Mohammadmosaferi KNaderi H(2021)AFIFComputer Communications10.1016/j.comcom.2021.05.025176:C(66-80)Online publication date: 1-Aug-2021
https://dl.acm.org/doi/10.1016/j.comcom.2021.05.025
Dakiche NBenbouzid-Si Tayeb FBenatchba KSlimani Y(2021)Tailored Network Splitting for Community Evolution Prediction in Dynamic Social NetworksNew Generation Computing10.1007/s00354-021-00122-6Online publication date: 3-Mar-2021
https://doi.org/10.1007/s00354-021-00122-6
Tsoukanara EKoloniari GPitoura E(2021)Should I Stay or Should I Go: Predicting Changes in Cluster MembershipWeb and Big Data. APWeb-WAIM 2021 International Workshops10.1007/978-981-16-8143-1_1(3-15)Online publication date: 4-Dec-2021
https://doi.org/10.1007/978-981-16-8143-1_1
Zhou QYu JSun W(2020)Formation of a Community: in the Case of a Particular Non-profit Sports Organization2020 International Conference on Computing, Networking and Communications (ICNC)10.1109/ICNC47757.2020.9049688(844-848)Online publication date: Feb-2020
https://doi.org/10.1109/ICNC47757.2020.9049688
Saganowski SBródka PKoziarski MKazienko P(2019)Analysis of group evolution prediction in complex networksPLOS ONE10.1371/journal.pone.022419414:10(e0224194)Online publication date: 29-Oct-2019
https://doi.org/10.1371/journal.pone.0224194
Koloniari GEvangelidis GSachpenderis NMilonas I(2019)A Framework for Predicting Community Behavior in Evolving Social NetworksProceedings of the 9th Balkan Conference on Informatics10.1145/3351556.3351583(1-4)Online publication date: 26-Sep-2019
https://dl.acm.org/doi/10.1145/3351556.3351583
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