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short-paper

Detecting opinion leaders and trends in online social networks

Authors:

Freimut Bodendorf,

Carolin KaiserAuthors Info & Claims

SWSM '09: Proceedings of the 2nd ACM workshop on Social web search and mining

Pages 65 - 68

https://doi.org/10.1145/1651437.1651448

Published: 02 November 2009 Publication History

Abstract

Today, online social networks in the World Wide Web become increasingly interactive and networked. Web 2.0 technologies provide a multitude of platforms, such as blogs, wikis, and forums where for example consumers can disseminate data about products and manufacturers. This data provides an abundance of information on personal experiences and opinions which are extremely relevant for companies and sales organizations. A new approach based on text mining and social network analysis is presented which allows detecting opinion leaders and opinion trends. This allows getting a better understanding of the opinion formation. The overall concept is presented and illustrated by an example.

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Cited By

Oueslati WMejri SAkaichi J(2024)A comprehensive study on social networks analysis and mining to detect opinion leadersInternational Journal of Computers and Applications10.1080/1206212X.2024.238065546:8(641-650)Online publication date: 26-Jul-2024
https://doi.org/10.1080/1206212X.2024.2380655
Mostafa M(2024)A social network analysis of the citation diffusion of academic articlesInternational Journal of Information Technology10.1007/s41870-024-02034-216:8(5055-5067)Online publication date: 25-Jun-2024
https://doi.org/10.1007/s41870-024-02034-2
Dai ZJiang WMcNickle C(2023)Social Network Analysis and Semantic Analysis of #TexasAbortionBan on TwitterSexuality Research and Social Policy10.1007/s13178-023-00848-621:2(591-597)Online publication date: 26-Jul-2023
https://doi.org/10.1007/s13178-023-00848-6
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Index Terms

Detecting opinion leaders and trends in online social networks
1. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Conferences

SWSM '09: Proceedings of the 2nd ACM workshop on Social web search and mining

November 2009

78 pages

ISBN:9781605588063

DOI:10.1145/1651437

General Chairs:
Irwin King
Chinese University of Hong Kong
,
Juanzi Li
Tsinghua University
,
Program Chairs:
Gui-rong Xue
Shanghai Jiaotong University
,
Jie Tang
Tsinghua University

Copyright © 2009 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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Publication History

Published: 02 November 2009

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CIKM '09

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CIKM '09: Conference on Information and Knowledge Management

November 2, 2009

Hong Kong, China

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CIKM '25

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Cited By

Oueslati WMejri SAkaichi J(2024)A comprehensive study on social networks analysis and mining to detect opinion leadersInternational Journal of Computers and Applications10.1080/1206212X.2024.238065546:8(641-650)Online publication date: 26-Jul-2024
https://doi.org/10.1080/1206212X.2024.2380655
Mostafa M(2024)A social network analysis of the citation diffusion of academic articlesInternational Journal of Information Technology10.1007/s41870-024-02034-216:8(5055-5067)Online publication date: 25-Jun-2024
https://doi.org/10.1007/s41870-024-02034-2
Dai ZJiang WMcNickle C(2023)Social Network Analysis and Semantic Analysis of #TexasAbortionBan on TwitterSexuality Research and Social Policy10.1007/s13178-023-00848-621:2(591-597)Online publication date: 26-Jul-2023
https://doi.org/10.1007/s13178-023-00848-6
Peng LChen TYang JCong T(2022)Management and Control of Enterprise Negative Network Public Opinion Dissemination Based on the Multi-Stakeholder Game Mechanism in ChinaSystems10.3390/systems1005014010:5(140)Online publication date: 5-Sep-2022
https://doi.org/10.3390/systems10050140
Bhattacharya SAgarwala ARoy S(2022)Mood detection and prediction using conventional machine learning techniques on COVID19 dataSocial Network Analysis and Mining10.1007/s13278-022-00957-x12:1Online publication date: 21-Sep-2022
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Deng WYang Y(2021)Cross-Platform Comparative Study of Public Concern on Social Media during the COVID-19 Pandemic: An Empirical Study Based on Twitter and WeiboInternational Journal of Environmental Research and Public Health10.3390/ijerph1812648718:12(6487)Online publication date: 16-Jun-2021
https://doi.org/10.3390/ijerph18126487
Liu YHuang WLuo D(2021)The reception of support in peer-to-peer online networks: Network position, support solicitation, and support provision in an online asthma caregivers groupHealth Informatics Journal10.1177/1460458221106602028:1Online publication date: 15-Dec-2021
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Mostafa M(2021)Mining halal food search pathways down the Wikipedia’s rabbit holeFood, Culture & Society10.1080/15528014.2021.1884452(1-21)Online publication date: 28-Apr-2021
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Nguyen VSi NBlanchet JDaumé HSingh A(2020)Robust Bayesian classification using an optimistic score ratioProceedings of the 37th International Conference on Machine Learning10.5555/3524938.3525617(7327-7337)Online publication date: 13-Jul-2020
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