Table Of ContentLecture Notes in Social Networks
Özgür Ulusoy
Abdullah Uz Tansel
Erol Arkun Editors
Recommendation
and Search in
Social Networks
Lecture Notes in Social Networks
Series editors
Reda Alhajj, University of Calgary, Calgary, AB, Canada
Uwe Glässer, Simon Fraser University, Burnaby, BC, Canada
Advisory Board
Charu Aggarwal, IBM T.J. Watson Research Center, Hawthorne, NY, USA
Patricia L. Brantingham, Simon Fraser University, Burnaby, BC, Canada
Thilo Gross, University of Bristol, UK
Jiawei Han, University of Illinois at Urbana-Champaign, IL, USA
Huan Liu, Arizona State University, Tempe, AZ, USA
Raúl Manásevich, University of Chile, Santiago, Chile
Anthony J. Masys, Centre for Security Science, Ottawa, ON, Canada
Carlo Morselli, University of Montreal, QC, Canada
Rafael Wittek, University of Groningen, The Netherlands
Daniel Zeng, The University of Arizona, Tucson, AZ, USA
More information about this series at http://www.springer.com/series/8768
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zg r Ulusoy Abdullah Uz Tansel
(cid:129)
Erol Arkun
Editors
Recommendation
and Search in
Social Networks
123
Editors
ÖzgürUlusoy ErolArkun
Department of Computer Engineering Department of Computer Engineering
Bilkent University Bilkent University
Ankara Ankara
Turkey Turkey
AbdullahUz Tansel
Department of Statistics andComputer
InformationSystems
Baruch College,CUNY
New York, NY
USA
ISSN 2190-5428 ISSN 2190-5436 (electronic)
Lecture Notesin SocialNetworks
ISBN 978-3-319-14378-1 ISBN 978-3-319-14379-8 (eBook)
DOI 10.1007/978-3-319-14379-8
LibraryofCongressControlNumber:2014959199
SpringerChamHeidelbergNewYorkDordrechtLondon
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Preface
This book is a timely collection of 12 chapters that present the state of the art in
various aspects of social search and recommendation systems. Within the broader
contextofsocialnetwork analysis, itfocusesonimportantandupcomingtopics of
socialsearchandrecommendationsystems.Webelievethatthebookisacoherent
collection of chapters which is not easily accomplished in edited volumes.
Many of the chapters are expanded versions of the best papers presented in the
IEEE/ACM International Conference on Advances in Social Networks Analysis
andMining(ASONAM’2013),whichwasheldinNiagaraFalls,CanadainAugust
2013. The papers were selected based on the reviews for the conference and then
were improved substantially by the authors. In addition to the selected papers, the
bookalsofeaturesinvitedchaptersinthefieldofsocialsearchandrecommendation
systems.
The first chapter, by Xinyue Wang, Laurissa Tokarchuk, Felix Cuadrado and
Stefan Poslad, presents an adaptive crawling model to detect emerging popular
topics,bysearchingforhighlycorrelateddatafortheeventsofinterest.Inthenext
chapter, Yuki Urabe, Rafal Rzepka, and Kenji Araki propose an emoticon rec-
ommendation system based on users’ emotional statements and evaluate its per-
formance in comparison to other such recommendation systems. Then, Georgios
Alexandridis, Giorgos Siolas, and Andreas Stafylopatis present a novel random
walk social recommendation approach based on rejection sampling.
In “Social Network Derived Credibility,” Erica Briscoe, Darren Appling and
Heather Hayes explore the use of social network properties as a basis for deter-
mining credibility. Inthenextchapter, Benjamin C.M.Fung, Yan’An Jin, Jiaming
Li, and Junqiang Liu propose a method to anonymize the social network with the
goalsofhidingtheidentitiesoftheparticipantsandpreservingthefrequentsharing
patterns within a community. In the following chapter, Cheng Chen, Kui Wu,
Venkatesh Srinivasan, and Xudong Zhang present a new detection mechanism,
usingbothsemanticandnonsemanticanalysis,toidentifyaspecialgroupofonline
users, called hidden paid posters.
In their work, Sogol Naseri, Arash Bahrehmand, and Chen Ding strive to
enhance recommendation accuracy through the use of a new similarity metric
v
vi Preface
whichisbasedonsocialtagginginformation.Theyalsopresentarecommendation
method that applies user similarity for finding the most interesting items to target
user’staste.AliKhodaei,CyrusShahabi,andSinaSohangirproposeanewmodel,
calledpersocialrelevancemodelutilizingsocialsignalstoimprovethewebsearch,
in their chapter titled “Personalization of Web Search Using Social Signals”.
Linhong Zhu, Sheng Gao, Sinno Jialin Pan, Haizhou Li, Dingxiong Deng, and
CyrusShahabiprovideaformulationfortheinformativesentenceselectionproblem
in opinion summarization as a community leader detection problem. Then, they
present new algorithms to identify communities and leaders.
ThechapterbyHasanShahidFerdous,MashruraTasnim,SaifAhmed,andMd.
TanvirAlamAnikexploresdifferencesinsearchinghabitsofthesocialnetworking
sitesindifferentregionsoftheworldbasedontheirlevelofeconomicdevelopment.
In“EvolutionaryInfluenceMaximizationinViralMarketing”,SanketNaikandQi
Yu propose a new framework to effectively apply viral marketing in a dynamic
socialnetwork.ThelastchapterbyAlessiaAmeliopresentsaninvestigationofthe
votingbehavioroftheItalianParliamentbyemployingmethodsindataminingand
network analysis fields.
We would like to express our appreciation to all contributing authors; without
their cooperation this book would not have been possible. Our special thanks are
duetoMs.PaulineLichtveldforhersupportandtoDr.TanselÖzyerwhodiligently
supported and coordinated the entire process of preparing this timely volume on
social network analysis.
Özgür Ulusoy
Abdullah Uz Tansel
Erol Arkun
Contents
Adaptive Identification of Hashtags for Real-Time Event Data
Collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Xinyue Wang, Laurissa Tokarchuk, Felix Cuadrado and Stefan Poslad
Comparison of Emoticon Recommendation Methods to Improve
Computer-Mediated Communication . . . . . . . . . . . . . . . . . . . . . . . . . 23
Yuki Urabe, Rafal Rzepka and Kenji Araki
Accuracy Versus Novelty and Diversity in Recommender Systems:
A Nonuniform Random Walk Approach . . . . . . . . . . . . . . . . . . . . . . 41
Georgios Alexandridis, Georgios Siolas and Andreas Stafylopatis
Social Network Derived Credibility . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Erica J. Briscoe, Darren Scott Appling and Heather Hayes
Anonymizing Social Network Data for Maximal Frequent-Sharing
Pattern Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Benjamin C.M. Fung, Yan’an Jin, Jiaming Li and Junqiang Liu
A Comprehensive Analysis of Detection of Online Paid Posters . . . . . . 101
Cheng Chen, Kui Wu, Venkatesh Srinivasan and Xudong Zhang
An Improved Collaborative Recommendation System
by Integration of Social Tagging Data . . . . . . . . . . . . . . . . . . . . . . . . 119
Sogol Naseri, Arash Bahrehmand and Chen Ding
Personalization of Web Search Using Social Signals . . . . . . . . . . . . . . 139
Ali Khodaei, Sina Sohangir and Cyrus Shahabi
vii
viii Contents
The Pareto Principle Is Everywhere: Finding Informative
Sentences for Opinion Summarization Through
Leader Detection. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
Linhong Zhu, Sheng Gao, Sinno Jialin Pan, Haizhou Li, Dingxiong Deng
and Cyrus Shahabi
Social Media Question Asking: A Developing Country Perspective. . . . 189
Hasan Shahid Ferdous, Mashrura Tasnim, Saif Ahmed
and Md. Tanvir Alam Anik
Evolutionary Influence Maximization in Viral Marketing . . . . . . . . . . 217
Sanket Anil Naik and Qi Yu
Mining and Analyzing the Italian Parliament: Party Structure
and Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
Alessia Amelio and Clara Pizzuti
Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 287
Contributors
Saif Ahmed BUET, Dhaka, Bangladesh
Georgios Alexandridis School of Electrical and Computer Engineering, National
Technical University of Athens, Zografou, Athens, Greece
Alessia Amelio Institute for High Performance Computing and Networking
(ICAR), National Research Council of Italy (CNR), Rende, CS, Italy
Md. Tanvir Alam Anik BUET, Dhaka, Bangladesh
Darren Scott Appling Georgia Tech, Atlanta, GA, USA
Kenji Araki Hokkaido University, Graduate School of Information Science and
Technology, Sapporo, Japan
Arash Bahrehmand Department of Information and Communications Technol-
ogies, Universitat Pompeu Fabra Barcelona, Barcelona, Spain
Erica J. Briscoe Georgia Tech, Atlanta, GA, USA
Cheng Chen University of Victoria, Victoria, Canada
Felix Cuadrado School of Electronic Engineering and Computer Science, Queen
Mary University of London, London, UK
Dingxiong Deng University of Southern California, Los Angeles, USA
Chen Ding Department of Computer Science, Ryerson University, Toronto,
Canada
Hasan Shahid Ferdous University of Melbourne, Parkville, VIC, Australia
Benjamin C.M. Fung McGill University, Montreal, QC, Canada
Sheng Gao Institute for Infocomm Research, Singapore, Singapore
ix
