Article

Discovering groups of people in Google news

Authors:

Daniel Gatica-PerezAuthors Info & Claims

HCM '06: Proceedings of the 1st ACM international workshop on Human-centered multimedia

Pages 55 - 64

https://doi.org/10.1145/1178745.1178757

Published: 27 October 2006 Publication History

Abstract

In this paper, we study the problem of content-based social network discovery among people who frequently appear in world news. Google news is used as the source of data. We describe a probabilistic framework for associating people with groups. A low-dimensional topic-based representation is first obtained for news stories via probabilistic latent semantic analysis (PLSA). This is followed by construction of semantic groups by clustering such representations. Unlike many existing social network analysis approaches, which discover groups based only on binary relations (e.g. co-occurrence of people in a news article), our model clusters people using their topic distribution, which introduces contextual information in the group formation process (e.g. some people belong to several groups depending on the specific subject). The model has been used to study evolution of people with respect to topics over time. We also illustrate the advantages of our approach over a simple co-occurrence-based social network extraction method.

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Cited By

Lopezosa CVállez MGuallar J(2024)La visión de Google News desde la academia: scoping reviewDoxa Comunicación. Revista Interdisciplinar de Estudios de Comunicación y Ciencias Sociales10.31921/doxacom.n38a1891Online publication date: 1-Jan-2024
https://doi.org/10.31921/doxacom.n38a1891
Hong JCha JG. BPark K(2023)Evaluation framework for facilitating the technology transfers of universities: Focusing on the perspective of technology donorsPLOS ONE10.1371/journal.pone.029395118:12(e0293951)Online publication date: 14-Dec-2023
https://doi.org/10.1371/journal.pone.0293951
Yao JCui BHuang YZhou Y(2018)Bursty event detection from collaborative tagsWorld Wide Web10.1007/s11280-011-0136-215:2(171-195)Online publication date: 25-Dec-2018
https://dl.acm.org/doi/10.1007/s11280-011-0136-2
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Discovering groups of people in Google news

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cover image ACM Conferences

HCM '06: Proceedings of the 1st ACM international workshop on Human-centered multimedia

October 2006

138 pages

ISBN:1595935002

DOI:10.1145/1178745

General Chairs:
Daniel Gatica-Perez
IDIAP Research Institute, Switzerland
,
Alejandro Jaimes
FXPAL Japan, Fuji Xerox, Co., Ltd., Japan
,
Nicu Sebe
University of Amsterdam, The Netherlands

Copyright © 2006 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: 27 October 2006

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MM06: The 14th ACM International Conference on Multimedia 2006

October 27, 2006

California, Santa Barbara, USA

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Cited By

Lopezosa CVállez MGuallar J(2024)La visión de Google News desde la academia: scoping reviewDoxa Comunicación. Revista Interdisciplinar de Estudios de Comunicación y Ciencias Sociales10.31921/doxacom.n38a1891Online publication date: 1-Jan-2024
https://doi.org/10.31921/doxacom.n38a1891
Hong JCha JG. BPark K(2023)Evaluation framework for facilitating the technology transfers of universities: Focusing on the perspective of technology donorsPLOS ONE10.1371/journal.pone.029395118:12(e0293951)Online publication date: 14-Dec-2023
https://doi.org/10.1371/journal.pone.0293951
Yao JCui BHuang YZhou Y(2018)Bursty event detection from collaborative tagsWorld Wide Web10.1007/s11280-011-0136-215:2(171-195)Online publication date: 25-Dec-2018
https://dl.acm.org/doi/10.1007/s11280-011-0136-2
De Nart DDegl’Innocenti DBasaldella MAgosti MTasso C(2016)A Content-Based Approach to Social Network Analysis: A Case Study on Research CommunitiesDigital Libraries on the Move10.1007/978-3-319-41938-1_15(142-154)Online publication date: 1-Jul-2016
https://doi.org/10.1007/978-3-319-41938-1_15
Traag VReinanda Rvan Klinken G(2016)Structure of a Media Co-occurrence NetworkProceedings of ECCS 201410.1007/978-3-319-29228-1_8(81-91)Online publication date: 4-May-2016
https://doi.org/10.1007/978-3-319-29228-1_8
Kwahk KKang E(2015)Management of duplicate members on websitesProceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 201510.1145/2808797.2808815(1104-1109)Online publication date: 25-Aug-2015
https://dl.acm.org/doi/10.1145/2808797.2808815
De Nart DDegl’Innocenti DPavan ABasaldella MTasso C(2015)Modelling the User Modelling Community (and Other Communities as Well)User Modeling, Adaptation and Personalization10.1007/978-3-319-20267-9_31(357-363)Online publication date: 11-Jun-2015
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Fang J(2014)Targeted Advertising Based on Social Network AnalysisApplied Mechanics and Materials10.4028/www.scientific.net/AMM.488-489.1306488-489(1306-1309)Online publication date: Jan-2014
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Au Yeung CIwata T(2011)Extracting multi-dimensional relationsProceedings of the 20th ACM international conference on Information and knowledge management10.1145/2063576.2063750(1203-1208)Online publication date: 24-Oct-2011
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Cucchiarelli AD’Antonio FVelardi P(2009)Analyzing Collaborations Through Content-Based Social NetworksComputational Social Network Analysis10.1007/978-1-84882-229-0_15(387-409)Online publication date: 6-Nov-2009
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