Conferences related to Social Network Analysis

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2023 Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted full papers will be peer reviewed. Accepted high quality papers will be presented in oral and poster sessions,will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE.


2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.


2018 17th International Conference on Information Technology Based Higher Education and Training (ITHET)

The convergence of current technologies provides the infrastructure for transmitting and storing information faster and cheaper. For information to be used in gaining knowledge, however, environments for collecting, storing, disseminating, sharing and constructing knowledge are needed. Such environments, knowledge media, brings together telecommunication, computer and networking technologies, learning theories and cognitive sciences to form meaningful environments that provides for a variety of learner needs. ITHET 2018 will continue with the traditional themes of previous events. However, our special theme for this year is a fundamental one. We have previously had MOOCs as our special theme, but now they are just infrastructure. Even “Blended Learning” is what we all do anyway. In a time of the unprecedented access to knowledge through IT, it is time for us to revisit the fundamental purpose of our educational system. It is certainly not about knowledge anymore.


2018 26th Signal Processing and Communications Applications Conference (SIU)

The general scope of the conference ranges from signal and image processing to telecommunication, and applications of signal processing methods in biomedical and communication problems.

  • 2017 25th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing and Communication Applications (SIU) conference is the most prominent scientific meeting on signal processing in Turkey bringing together researchers working in signal processing and communication fields. Topics include but are not limited to the areas of research listed in the keywords.

  • 2016 24th Signal Processing and Communication Application Conference (SIU)

    Signal Processing Theory, Statistical Signal Processing, Nonlinear Signal Processing, Adaptive Signal Processing, Array and Multichannel Signal Processing, Signal Processing for Sensor Networks, Time-Frequency Analysis, Speech / Voice Processing and Recognition, Computer Vision, Pattern Recognition, Machine Learning for Signal Processing, Human-Machine Interaction, Brain-Computer Interaction, Signal-Image Acquisition and Generation, image Processing, video Processing, Image Printing and Presentation, Image / Video / Audio browsing and retrieval, Image / Video / Audio Watermarking, Multimedia Signal Processing, Biomedical Signal Processing and Image Processing, Bioinformatics, Biometric Signal-Image Processing and Recognition, Signal Processing for Security and Defense, Signal and Image Processing for Remote Sensing, Signal Processing Hardware, Signal Processing Education, Radar Signal Processing, Communication Theory, Communication Networks, Wireless Communications

  • 2015 23th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing Theory Statistical Signal Processing Nonlinear Signal Processing Adaptive Signal Processing Array and Multichannel Signal Processing Signal Processing for Sensor Networks Time-Frequency Analysis Speech / Voice Processing and Recognition Computer Vision Pattern Recognition Machine Learning for Signal Processing Human-Machine Interaction Brain-Computer Interaction Signal-Image Acquisition and Generation image Processing video Processing Image Printing and Presentation Image / Video / Audio browsing and retrieval Image / Video / Audio Watermarking Multimedia Signal Processing Biomedical Signal Processing and Image Processing Bioinformatics Biometric Signal-Image Processing and Recognition Signal Processing for Security and Defense Signal and Image Processing for Remote Sensing Signal Processing Hardware Signal Processing Education Radar Signal Processing Communication Theory Communication Networks Wireless Communications

  • 2014 22nd Signal Processing and Communications Applications Conference (SIU)

    SIU will be held in Trabzon, Turkey at the Karadeniz Technical University Convention and Exhibition Centre on April 23, 2014. SIU is the largest and most comprehensive technical conference focused on signal processing and its applications in Turkey. Last year there were 500 hundred participants. The conference will feature renowned speakers, tutorials, and thematic workshops. Topics include but are not limited to: Signal Procesing, Image Processing, Communication, Computer Vision, Machine Learning, Biomedical Signal Processing,

  • 2013 21st Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2012 20th Signal Processing and Communications Applications Conference (SIU)

    Conference will discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. Conference will also include invited lectures, tutorials and special sessions.

  • 2011 19th Signal Processing and Communications Applications Conference (SIU)

    Conference will bring together academia and industry professionals as well as students and researchers to present and discuss state of the art solutions and research results on existing and future DSP and telecommunication systems, applications, and related standardization activities. The Conference will also include invited lectures, tutorials and special sessions.

  • 2010 IEEE 18th Signal Processing and Communications Applications Conference (SIU)

    S1.Theory of Signal-Processing S2.Statistical Signal-Processing S3.Multimedia Signal-Processing S4.Biomedical Signal-Processing S5.Sensor Networks S6.Multirate Signal-Processing S7.Pattern Recognition S8.Computer Vision S9.Adaptive Filters S10.Image/Video/Speech Browsing, Retrieval S11.Speech/Audio Coding S12.Speech Processing S13.Human-Machine Interfaces S14.Surveillance Signal Processing S15.Bioinformatics S16.Self-Learning S17.Signal-Processing Education S18.Signal-Processing Systems S1

  • 2009 IEEE 17th Signal Processing and Communications Applications Conference (SIU)

    The scope of the conference is to cover recent topics in theory and applications of Signal Processing and Communications.

  • 2008 IEEE 16th Signal Processing and Communications Applications Conference (SIU)

    Signal Processing, Image Processing, Speech Processing, Pattern Recognition, Human Computer Interaction, Communication, Video and Speech indexing, Computer Vision, Biomedical Signal Processing

  • 2007 IEEE 15th Signal Processing and Communications Applications (SIU)

  • 2006 IEEE 14th Signal Processing and Communications Applications (SIU)

  • 2005 IEEE 13th Signal Processing and Communications Applications (SIU)

  • 2004 IEEE 12th Signal Processing and Communications Applications (SIU)


2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT)

ICALT is an annual international conference on Advanced Learning Technologies and Technology-enhanced Learning organized by the IEEE Technical Committee on Learning Technology. It aims to bring together people who are working on the design, development, use and evaluation of technologies that will be the foundation of the next generation of e-learning systems and technology-enhanced learning environments.


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Periodicals related to Social Network Analysis

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Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Communications Magazine, IEEE

IEEE Communications Magazine was the number three most-cited journal in telecommunications and the number eighteen cited journal in electrical and electronics engineering in 2004, according to the annual Journal Citation Report (2004 edition) published by the Institute for Scientific Information. Read more at http://www.ieee.org/products/citations.html. This magazine covers all areas of communications such as lightwave telecommunications, high-speed data communications, personal communications ...


Communications Surveys & Tutorials, IEEE

Each tutorial reviews currents communications topics in network management and computer and wireless communications. Available tutorials, which are 2.5 to 5 hours in length contains the original visuals and voice-over by the presenter. IEEE Communications Surveys & Tutorials features two distinct types of articles: original articles and reprints. The original articles are exclusively written for IEEE Communications Surveys & Tutorials ...


Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


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Most published Xplore authors for Social Network Analysis

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Xplore Articles related to Social Network Analysis

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Social network analysis algorithm on a many-core GPU

2012 Fourth International Conference on Ubiquitous and Future Networks (ICUFN), 2012

Proliferation of social network service permeates lives of people on internet, and its social, political and cultural significance prompts the need to understand and to analyze the contents and structures of such services. The sheer volume of such social network is enormous, and it necessitates development and implementation of efficient social network analysis algorithms. Among these, Influence Maximization is one ...


An Integrated Home Financial Investment Learning Environment Applying Cloud Computing in Social Network Analysis

2011 International Conference on Advances in Social Networks Analysis and Mining, 2011

This paper tried to apply cloud computing technology in social network analysis for a comprehensive home financial learning environment that individual investors may use as a reference in establishing web-based learning and investment platforms. The major contributions were described in three parts. First, this paper advanced the social network analysis technology to be able to handle millions of nodes and ...


A Fuzzy Approach to Social Network Analysis

2009 International Conference on Advances in Social Network Analysis and Mining, 2009

Adjacency relations for social network analysis have usually been tackled in their bidimensional form, in the sense that relations are computed over pairs of objects. Nevertheless, this paper considers the bidimensional case as restrictive and it proposes an approach where the dimension of the analysis is not limited to binary relations. With the aid of fuzzy logic and OWA operators, ...


RDF approach on social network analysis

2016 International Conference on Research Advances in Integrated Navigation Systems (RAINS), 2016

The first W3 Consortium standard to represent metadata with rich amount of information resource of the web is referred as Resource Description Framework (RDF). RDF semantic web approaches are used on different areas of research today such as social network analysis, discovering semantic associations, semantic web engineering and so on. Social networking in modern society is a communication mechanism to ...


Cancelable fusion using Social Network Analysis

2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013), 2013

In this paper, novel cancelable biometric template generation algorithm using Social Network Analysis is presented. Two sets of features are fused using Social Network. Proposed fusion technique is cancelable. Eigenvector centrality is used to generate final sets of features from the Virtual Social Network (VSN). The domain transformation of features using VSN confirms the cancelability in biometric template generation.


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Educational Resources on Social Network Analysis

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IEEE.tv Videos

IEEE Themes - Efficient networking services underpin social networks
Panelist Yuval Elovici - ETAP Forum Tel Aviv 2016
Network Analysis: RF Boot Camp
IEEE Themes - Science of Social Networking
Fuzzy Sets and Social Research - Charles C. Ragin - WCCI 2016
IEEE Themes - Distance-Dependent Kronecker Graphs For Modeling Social Networks
Integrated Access and Backhaul in 5G - Navid Abedini - IEEE Sarnoff Symposium, 2019
IEEE Themes - Social Networks: Dynamic Social Interaction Data
IMS MicroApp: Causality Considerations for Multi-Gigabit StatEye Analysis
IEEE Themes - Social dynamics in peer-to-peer sharing networks
Michele Nitti: Searching the Social Internet of Things by Exploiting Object Similarity - Special Session on SIoT: WF-IoT 2016
Optimizing Service Delivery at the Mobile Network Edge - Leandros Tassliuas - IEEE Sarnoff Symposium, 2019
A Comparator Design Targeted Towards Neural Net - David Mountain - ICRC San Mateo, 2019
Optical Stealth Communication based on Amplified Spontaneous Emission Noise - Ben Wu - IEEE Sarnoff Symposium, 2019
A Conversation with…Richard Mallah: IEEE TechEthics
IEEE Themes - Five incentive schemes for peer-to-peer networks
Risto Miikkilainen - Multiagent Learning Through Neuroevolution
IMS 2011 Microapps - Yield Analysis During EM Simulation
IMS 2012 Microapps - Improve Microwave Circuit Design Flow Through Passive Model Yield and Sensitivity Analysis
IMS 2011 Microapps - A Practical Approach to Verifying RFICs with Fast Mismatch Analysis

IEEE-USA E-Books

  • Social network analysis algorithm on a many-core GPU

    Proliferation of social network service permeates lives of people on internet, and its social, political and cultural significance prompts the need to understand and to analyze the contents and structures of such services. The sheer volume of such social network is enormous, and it necessitates development and implementation of efficient social network analysis algorithms. Among these, Influence Maximization is one example of such algorithm. The objective of the influence maximization algorithm is to find a small subset of nodes, so-called seed-nodes, that result in maximization of the spread of influence through the edges in the graph which represents connections in social network. As the cost-efficient, high-performance computing power of many-core GPUs is widely utilized in nearly all areas of computing, we apply our expertise in GPU parallelization to the influence maximization algorithm. The graph algorithms are known as one of sparse algorithms since its irregular data structure requires indirect accesses to memory, resulting in lowbandwidth memory access. Sparse algorithms are one area where many researchers are focused on its efficient parallelization, because the usage of such algorithms is universal and thus, vital to broad application areas, from scientific simulations to social studies. In this paper, we introduce algorithms to compute influence maximization of social network, and adopt this algorithm to fit parallel implementation on many-core GPU. We also analyze our implementations in terms of factors affecting GPU performance.

  • An Integrated Home Financial Investment Learning Environment Applying Cloud Computing in Social Network Analysis

    This paper tried to apply cloud computing technology in social network analysis for a comprehensive home financial learning environment that individual investors may use as a reference in establishing web-based learning and investment platforms. The major contributions were described in three parts. First, this paper advanced the social network analysis technology to be able to handle millions of nodes and links. Second, we demonstrate how cloud computing can be applied to advanced computing in social network. Third, we performed several intelligent analyses on a very popular social network, IHFILE, to identify some interesting and important features of it. In addition to analyzing a homogeneous social network such as IHFILE, we also propose direction of how cloud computing can be performed on a social network analysis as our future work.

  • A Fuzzy Approach to Social Network Analysis

    Adjacency relations for social network analysis have usually been tackled in their bidimensional form, in the sense that relations are computed over pairs of objects. Nevertheless, this paper considers the bidimensional case as restrictive and it proposes an approach where the dimension of the analysis is not limited to binary relations. With the aid of fuzzy logic and OWA operators, it is showed that the interpretation of m-ary adjacency relations is the same of binary relations and therefore they can consistently be employed in social network analysis and some novel results be derived. Besides justifying the use of m-ary relations, the paper proposes a way to characterize them and, eventually, it will provide the reader with an example section.

  • RDF approach on social network analysis

    The first W3 Consortium standard to represent metadata with rich amount of information resource of the web is referred as Resource Description Framework (RDF). RDF semantic web approaches are used on different areas of research today such as social network analysis, discovering semantic associations, semantic web engineering and so on. Social networking in modern society is a communication mechanism to generate large amount of user data in real time. Key features and soul of social network can be exploited via Social Network Analysis (SNA). SNA used to extract network of interactions between organizations, peoples and transactions. Recent studies shows semantic web technologies are used to build up applications that can analyze data on various social networking sites. In this paper different types of RDF representations and various social network analysis methods using RDF are studied.

  • Cancelable fusion using Social Network Analysis

    In this paper, novel cancelable biometric template generation algorithm using Social Network Analysis is presented. Two sets of features are fused using Social Network. Proposed fusion technique is cancelable. Eigenvector centrality is used to generate final sets of features from the Virtual Social Network (VSN). The domain transformation of features using VSN confirms the cancelability in biometric template generation.

  • Social Network Analysis in IT Company

    The goal of social network analysis is to study human relations and social structures. This article first introduces the concept of social network analysis and then discusses the analysis steps in detail with the illustration of two companies. Finally this article draws a conclusion by comparing the different business processes after using the social network analysis approach design.

  • Ontology of moodle e-learning system for social network analysis

    The analysis using Social Network Analysis (SNA) is focusing more on the number or the frequency of social interactions based on adjacency matrix. This method cannot be used to observe the semantic relationship among e-Learning components. Therefore, this paper aims to propose a new paradigm of Social Network Analysis (SNA) using ontology structure of Moodle e-Learning. By considering the relationship of ontology, we can understand the meaning of semantic relationship more deeply. The ontology of Moodle e-learning system for social network analysis will become great advantage to make measurement not only based on the matrix or number of interactions but also based on the semantic meaning of the relationships among users.

  • Discovering and analyzing learning pattern on web based learning using social network analysis

    Web based learning has been promoting alternative way of learning for decades. The difficulty of web based learning is to provide the appropriate support for the learners so that the learners will not get lost and their learning achievements can be ensured. This paper thus proposes the method for discovering learning patterns of the learners on web based learning particularly for ensuring the learning achievement. The learning pattern is discovered by analyzing the interactions among the learners and the learning objects with social network analysis. Then, the achievement learning pattern is finally determined by analyzing the sets of obtained social network measurements. The interaction data is gathered from online course named introduction to Information Technology in the 2013 academic year, particularly for spreadsheet content module having 10 learning objects. The interaction patterns only of two groups of students including scientific and nonscientific background knowledge who pass the spreadsheet examination are analyzed. Finally, learning patterns ensuring learning achievement for spreadsheet content module of those students having different background knowledge is revealed.

  • Social Network Analysis Application in Bulletin Board Systems

    A social network is a map of the relationships between individuals where we can observe their social activities. Conception of centrality comes from structural sociology. It is a fundamental method in the social network analysis. Centrality is a fundamental concept in network analysis. It usually is used to identify the "most important" ones in a social network. Bulletin board system is an important way for human communication. It is important to appoint appropriate moderator for each board in the bulletin board system. It'll influence the running efficiency of the BBS from several aspects. This paper introduces centrality measures into the appointment of moderator for bulletin board systems. To fulfill above aim, a social network named BBS network is built for each board in a bulletin board system. Each node denotes a user for the bulletin board system. Several methods are used to compute centrality value of each node in the BBS network. The nodes with highest centrality may be the right users to play the moderator roles. The computing results can also be used to judge if current moderators work well.

  • Semantic web wiki: Social network analysis of page editing

    This paper presents experiments with applying social network analysis on data about editing of semantic media wiki. As a number of users are editing the same wiki pages, one can view them as a social network of people interacting via wiki pages. We propose representation of the wiki editing log files as a graph either of users that are connected if they are editing the same pages or of pages that are connected if edited by the same users. We apply social network analysis on such graphs in order to provide some insights into activity of the editors of semantic wiki pages.



Standards related to Social Network Analysis

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Jobs related to Social Network Analysis

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