The Second International Workshop on Social Networks Analysis, Management and Security
(SNAMS - 2015)

in conjunction with

The 3rd International Conference on Future Internet of Things and Cloud (FiCloud-2015)

24-26 August 2015, Rome, Italy

                

 

Social network analysis is concerned with the study of relationships between social entities. The recent advances in internet technologies and social media sites, such as Facebook, Twitter and LinkedIn, have created outstanding opportunities for individuals to connect, communicate or comment on issues or events of their interests. Social networks are dynamic and evolving in nature; they also involve a huge number of users. Frequently, the information related to a certain concept is distributed among several servers. This brings numerous challenges to researchers, particularity in the data mining and machine learning fields. The purpose of this workshop is to provide a forum for researchers to present and discuss their work which is related to social network analysis. This workshop is col-located with the 3rd International Conference on Future Internet of Things and Cloud (FiCloud-2015), 24-26 August 2015, Barcelona, Spain

Proceedings of the workshops will be published by the IEEE Conference Publishing Services (CPS) and will be included in the IEEE-Xplore and the IEEE Computer Society (CSDL) digital libraries. These are also indexed through IEE INSPEC, EI (Compendex), Thomson ISI.


Topics of interest
==============
Authors are encouraged to submit their original work, which is not submitted elsewhere, to this workshop. The topics of the workshop include but not limited to:

  • Social networks mining
  • Social networks security and privacy
  • Social networks architecture and growth
  • Social networks visualization and large scale data representation
  • Geographical aspects of social networks
  • Social networks and big data
  • Impact of social networks
  • Social networks data analysis tools and services on the Cloud
  • Opinion mining
  • Sentimental analysis
  • Community formation, analysis and detection in Social networks
  • Anomaly detection in social network evolution
  • Personalization of search engines and recommender systems based on social network behavior
  • Psychological and criminal studies related to social networks and social networks behavior
  • Graphical visualization and analysis of social networks
  • Natural language processing applications/studies on social networks

Paper Submission :
=============

Authors are requested to submit papers reporting original research results and experience. The page limit for full papers is 6 pages. Papers should be prepared using IEEE two-column template.

IEEE Computer Society Proceedings Author Guidelines are available at: IEEE Guidelines Link

Papers should be submitted as PDF files via the EasyChair: EasyChair Link

Submitted research papers may not overlap with papers that have already been published or that are simultaneously submitted to a journal or a conference. All papers accepted for this conference are peer-reviewed and are to be published in the conference proceedings by the IEEE Computer Society Conference Publishing Service (CPS), and indexed by IEEE Xplore Digital Library

Accepted papers will be invited to submit extended versions to the Special Issues in the follwoing journals

  • International Journal of Virtual Communities and Social Networking (IJVCSN) Link
  • International Journal of Social Network Mining Link

Important Dates :
=============

Full Paper Submission:  May 01st, 2015
Notification of Decision:  May 25th, 2015
Registration and Camera-Ready: June 20th, 2015

Organising Committee

General co-Chairs:

  • Keith C.C. Chan, The Hong Kong Polytechnic University, Hong Kong
  • Rehab Duwairi, Jordan University of Science and Technology, Jordan.

Technical Program co-Chairs:

  • Zaki Malik, Wayne State University, USA
  • Ahmed Abdeen Hamed, University of Vermont, USA

Publication Chair:

  • Tolga Soyata, University of Rochester, USA
  • Elhadj Benkhelifa, Staffordshire University, UK

    Organising Chair:

  • Yaser Jararweh, Jordan Univeristy of Science and Technology (yijararweh@just.edu.jo)

SNAMS Steering Committee:

  • Mahmoud Al-Ayyoub, Jordan University of Science and Technology, Jordan
  • Jie Gao, Stony Brook University, USA
  • Bas Geerdink, ING, Netherlands
  • Kami Makki, Lamar University, USA
  • Bhavani Thuraisingham, The University of Texas at Dallas, USA
  • Elhadj Benkhelifa, Staffordshire University, UK

Program: TUESDAY 25 AUGUST 2015

    SNAMS Keynote Session 1 (13.30-15:00):
    Session Chair: Rehab Duwairi, Jordan University of Science and Technology, Jordan

  • CLOUD-CENTRIC ASSURED INFORMATION SHARING FOR SECURE SOCIAL NETWORKING AND INTERNET OF THINGS 
    Bhavani Thuraisingham, The University of Texas at Dallas, USA

    SNAMS Session 2: Social Networks I  (15:30-17:00)
    Session Chair: Rehab Duwairi, Jordan University of Science and Technology, Jordan
    Room: Raffaello A

  • New centrality measure in Social Networks based on Independent Cascade (IC) model
    Ibrahima Gaye, Gervais Mendy, Samuel Ouya and Diaraf Seck
  • Improved Burst Based Real-time Event Detection using Location Dependent Corpora
    Jürgen Nützel and Frank Zimmermann
  • Different Models to Visualise Geolocated City Data from Social Networks
    Taras Agryzkov, Francisco Álvarez, Leticia Serrano-Estrada, Leandro Tortosa and José F. Vicent
  • Social Opinion Mining : An Approach for Italian Language
    Vito Santarcangelo, Giuseppe Oddo, Maria Pilato, Fabrizio Valenti and Claudio Fornaro
  • Graph Summarization for Hashtag Recommendation
    Mohammed Al-Dhelaan and Hadel Alhawasi
  • Using a Rich Context Model for People-to-People Recommendation
    Alisa Sotsenko, Marc Jansen and Marcelo Milrad

    SNAMS Session 3: Social Networks II  (17:00-18:30)
    Session Chair: Muhannad Quwaider, Jordan University of Science and Technology, Jordan
    Room: Raffaello A

  • RUM Extractor: A Facebook Extractor for Data Analysis
    Rehab M Duwairi and Mosab AlFaqeeh
  • Visualizing Social Network Data: a comparative study of Asian-American student conferences
    Roberto Palmieri and Carlo Giglio
  • Reliability of the closed-chain-fan social network
    Hajar Sahbani and Mohamed El Marraki
  • Human Annotated Arabic Dataset of Book Reviews for Aspect Based Sentiment Analysis
    Mohammad AL-Smadi, Omar Qawasmeh, Bashar Talafha and Muhannad Quwaider
  • Negation-aware Framework for Sentiment Analysis in Arabic Reviews
    Rehab M. Duwairi and Mohammad A. Alshboul
  • Ontology-Based Approach for Temporal Semantic Modelling of Social Networks
    Souâad Boudebza,Fiaçal Azouaou and Omar Nouali

    Keynote Speaker: PROF. BHAVANI THURAISINGHAM

    Dr. Bhavani Thuraisingham is the Louis A. Beecherl, Jr. Distinguished Professor of Computer Science and the Executive Director of the Cyber Security Research and Education Institute (CSI) at The University of Texas at Dallas. She is an elected Fellow of IEEE, the AAAS, the British Computer Society, and the SPDS (Society for Design and Process Science). She received several prestigious award including IEEE Computer Society's 1997 Technical Achievement Award for “outstanding and innovative contributions to secure data management”, the 2010 ACM SIGSAC (Association for Computing Machinery, Special Interest Group on Security, Audit and Control) Outstanding Contributions Award for “seminal research contributions and leadership in data and applications security for over 25 years” and the SDPS Transformative Achievement Gold Medal for her contributions to interdisciplinary research. She has unique experience working in the commercial industry (Honeywell), federal research laboratory (MITRE), US government (NSF) and academia and her 35 year career includes research and development, technology transfer, product development, program management, and consulting for the federal government. Her work has resulted in 100+ journal articles, 200+ conference papers, 100+ keynote and featured addresses, eight US patents (three pending) and fifteen books (two pending). She received the prestigious earned higher doctorate degree (DEng) from the University of Bristol England in 2011 for her published work in secure data management since her PhD. She has been a strong advocate for women in computing and has delivered featured addresses at events organized by the CRA-W (Computing Research Association) and SWE (Society for Women Engineers).

    ABSTRACT: CLOUD-CENTRIC ASSURED INFORMATION SHARING FOR SECURE SOCAL NETWORKING AND INTERNET OF THINGS This presentation will describe our research and development efforts in assured cloud computing for the Air Force Office of Scientific Research. We have developed a secure cloud computing framework as well as multiple secure cloud query processing systems. Our framework uses Hadoop to store and retrieve large numbers of RDF triples by exploiting the cloud computing paradigm and we have developed a scheme to store RDF data in a Hadoop Distributed File System. We implemented XACML-based policy management and integrated it with our query processing strategies. For secure query processing with relational data we utilized the HIVE framework. More recently we have developed strategies for secure storage and query processing in a hybrid cloud. In particular, we have developed algorithms for query processing wherein user’s local computing capability is exploited alongside public cloud services to deliver an efficient and secure data management solution. We have also developed techniques for secure virtualization using the XEN hypervisor to host our cloud data managers as well as an RDF-based policy engine hosted on our cloud computing framework. Finally we have developed a secure social media framework hosted on our secure cloud computing framework. The presentation will discuss our secure cloud computing framework for assured information sharing and discuss the secure social media framework. We will then discuss the relationship to big data security and privacy aspects and connect our research to Secure Internet of Things with a special emphasis on data privacy.