Pub Date : 2011-12-01DOI: 10.1109/CASON.2011.6085945
Katarina Gavric, D. Culibrk, Milan Mirković, V. Crnojevic
An increasing amount of publicly available geo-referenced data enables the identification of patterns of behavior, habits and movements of people. This paper presents results of a case study analysis based on data ser containing publicly available geo-referenced videos downloaded from YouTube, tagged as recorded in Africa. Our goal was to determine major routes of movement across the continent, to determine when people start their trip and the basic means of transportation used. The paper presents results of the analysis conducted on 113.157 unique YouTube records. We were able to identify major travel routes, directions, carriers and even flights favored by people traveling across Africa, information that is potentially valuable to disease outbreak management, airline industry, etc.
{"title":"Using YouTube data to analyze human continent-level mobility","authors":"Katarina Gavric, D. Culibrk, Milan Mirković, V. Crnojevic","doi":"10.1109/CASON.2011.6085945","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085945","url":null,"abstract":"An increasing amount of publicly available geo-referenced data enables the identification of patterns of behavior, habits and movements of people. This paper presents results of a case study analysis based on data ser containing publicly available geo-referenced videos downloaded from YouTube, tagged as recorded in Africa. Our goal was to determine major routes of movement across the continent, to determine when people start their trip and the basic means of transportation used. The paper presents results of the analysis conducted on 113.157 unique YouTube records. We were able to identify major travel routes, directions, carriers and even flights favored by people traveling across Africa, information that is potentially valuable to disease outbreak management, airline industry, etc.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130910998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/CASON.2011.6085931
K. Halimi, H. Seridi-Bouchelaghem, C. Faron-Zucker
We have assisted the development of a significant number of e-learning systems, which have achieved great success in distance teaching and education, but most of these systems present some limitations and some disadvantages. Most of them are closed where learning resources are fixed and the adaptability, the flexibility, and social relations are ignored and in most cases are not taken into account at all, actors of such systems tend to have a minimal collaborative navigation, awareness features and social relations analysis and they often find themselves isolated without sensing what the rest of learning community is doing. Significantly, new technologies had recently emerged: the social concepts and the social awareness features leading significant change to collaboration and learning. These emerging technologies are increasingly being adopted to improve remote education and providing better enhancement for learning. These improvements are offered to students who, regardless of their computer systems, can collaborate to improve their cognitive and social skills. In this article, we present the concepts of a new learning paradigm: CSSL (Computer Supported Social Learning) and we have implemented a first prototype called SoLearn that groups some of those concepts. SoLearn (A Social Learning Network) aims to provide its users with a new learning experience based on social networks and enhanced with social awareness concepts.
我们已经帮助开发了大量的电子学习系统，这些系统在远程教学和教育中取得了巨大的成功，但大多数这些系统都存在一些局限性和一些缺点。其中大多数是封闭的，学习资源是固定的，适应性、灵活性和社会关系被忽视，在大多数情况下根本没有考虑到，这些系统的参与者往往具有最小的协作导航、意识特征和社会关系分析，他们经常发现自己被孤立，而不知道学习社区的其他成员在做什么。值得注意的是，最近出现了新的技术:社会概念和社会意识特征导致了协作和学习的重大变化。这些新兴技术越来越多地被用于改善远程教育，并为学习提供更好的增强。这些改进提供给学生，无论他们的计算机系统如何，都可以合作提高他们的认知和社交技能。在本文中，我们提出了一种新的学习范式的概念:CSSL(计算机支持的社会学习)，并实现了一个名为SoLearn的原型，该原型将其中的一些概念进行了分组。SoLearn (A Social Learning Network)旨在为用户提供基于社交网络并增强社会意识概念的全新学习体验。
{"title":"Solearn: A Social Learning Network","authors":"K. Halimi, H. Seridi-Bouchelaghem, C. Faron-Zucker","doi":"10.1109/CASON.2011.6085931","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085931","url":null,"abstract":"We have assisted the development of a significant number of e-learning systems, which have achieved great success in distance teaching and education, but most of these systems present some limitations and some disadvantages. Most of them are closed where learning resources are fixed and the adaptability, the flexibility, and social relations are ignored and in most cases are not taken into account at all, actors of such systems tend to have a minimal collaborative navigation, awareness features and social relations analysis and they often find themselves isolated without sensing what the rest of learning community is doing. Significantly, new technologies had recently emerged: the social concepts and the social awareness features leading significant change to collaboration and learning. These emerging technologies are increasingly being adopted to improve remote education and providing better enhancement for learning. These improvements are offered to students who, regardless of their computer systems, can collaborate to improve their cognitive and social skills. In this article, we present the concepts of a new learning paradigm: CSSL (Computer Supported Social Learning) and we have implemented a first prototype called SoLearn that groups some of those concepts. SoLearn (A Social Learning Network) aims to provide its users with a new learning experience based on social networks and enhanced with social awareness concepts.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"516 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133167173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/CASON.2011.6085958
K. Wegrzyn-Wolska, L. Bougueroua, G. Dziczkowski
The quantity of medical publications in the media such a tweets, blogs, and another content in social media is growing at an exponential rate. Exploring and analyzing this content has become a necessity. The objective of this paper is to discuss the variety of issues and challenges surrounding the perspectives regarding the use of Social Network Analyses and Text Mining methods for applications in E health and medecine. The article will first look at the directions taken in Social Media and Text Mining for medical science. First we present a review of the literature in Social Media and Text Mining analysis for medical purposes and then describe the work done for our prediction system for collecting and manipulating and Twitter data.
{"title":"Social media analysis for e-health and medical purposes","authors":"K. Wegrzyn-Wolska, L. Bougueroua, G. Dziczkowski","doi":"10.1109/CASON.2011.6085958","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085958","url":null,"abstract":"The quantity of medical publications in the media such a tweets, blogs, and another content in social media is growing at an exponential rate. Exploring and analyzing this content has become a necessity. The objective of this paper is to discuss the variety of issues and challenges surrounding the perspectives regarding the use of Social Network Analyses and Text Mining methods for applications in E health and medecine. The article will first look at the directions taken in Social Media and Text Mining for medical science. First we present a review of the literature in Social Media and Text Mining analysis for medical purposes and then describe the work done for our prediction system for collecting and manipulating and Twitter data.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133289005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/CASON.2011.6085932
M. Kamola, E. Niewiadomska-Szynkiewicz, B. Piech
Real-life call detail data (CDR) are used to build a graph of a social network of telecommunication operator customers. Affiliation network is used in graph construction since CDR data are partially kept anonymous. A number of the resulting network properties are examined to prove the correctness of the graph construction algorithm. Cliques in the network and network dynamics are analyzed; suggestions are given about possible utilization of the obtained information in the operation of a telecommunication operator.
{"title":"Reconstruction of a social network graph from incomplete call detail records","authors":"M. Kamola, E. Niewiadomska-Szynkiewicz, B. Piech","doi":"10.1109/CASON.2011.6085932","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085932","url":null,"abstract":"Real-life call detail data (CDR) are used to build a graph of a social network of telecommunication operator customers. Affiliation network is used in graph construction since CDR data are partially kept anonymous. A number of the resulting network properties are examined to prove the correctness of the graph construction algorithm. Cliques in the network and network dynamics are analyzed; suggestions are given about possible utilization of the obtained information in the operation of a telecommunication operator.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131077178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/CASON.2011.6085946
Vincent Levorato, Coralie Petermann
A lot of algorithms in communities detection have been proposed particularly for undirected networks. As methods to find communities in directed networks are few, our contribution is to propose a method based on strongly and unilaterally connected components, and more specifically on strongly p-connected components in directed graphs. The result is a clustering of nodes giving good results in generated graphs according to several clustering evaluation measures, and which practical time complexity remains acceptable.
{"title":"Detection of communities in directed networks based on strongly p-connected components","authors":"Vincent Levorato, Coralie Petermann","doi":"10.1109/CASON.2011.6085946","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085946","url":null,"abstract":"A lot of algorithms in communities detection have been proposed particularly for undirected networks. As methods to find communities in directed networks are few, our contribution is to propose a method based on strongly and unilaterally connected components, and more specifically on strongly p-connected components in directed graphs. The result is a clustering of nodes giving good results in generated graphs according to several clustering evaluation measures, and which practical time complexity remains acceptable.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133485189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/CASON.2011.6085930
L. Menezes, Andryw Marques Ramos, Ana Gabrielle Ramos Falcão, C. Baptista, Hugo Feitosa de Figueirêdo
Web 2.0 allows users to freely publish information regarding several subjects. Social content websites may take advantage of such by creating means for dissemination and creation of collaborative knowledge. However, an adequate environment is needed for the insertion of such information on social content websites. Mobile 2.0 incorporates some Web 2.0 concepts on mobile platforms using context-aware information captured from sensors, like GPS. This paper presents a model based on social content websites that uses context ontologies for the provision of personalized services on mobile platforms.
Web 2.0允许用户自由发布关于多个主题的信息。社交内容网站可以通过创建协作知识的传播和创造手段来利用这种优势。然而，这些信息在社交内容网站上的插入需要一个足够的环境。Mobile 2.0在移动平台上结合了一些Web 2.0概念，使用从传感器(如GPS)捕获的上下文感知信息。本文提出了一个基于社交内容网站的模型，该模型使用上下文本体在移动平台上提供个性化服务。
{"title":"Context and social networks interaction modeling for context aware alert systems","authors":"L. Menezes, Andryw Marques Ramos, Ana Gabrielle Ramos Falcão, C. Baptista, Hugo Feitosa de Figueirêdo","doi":"10.1109/CASON.2011.6085930","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085930","url":null,"abstract":"Web 2.0 allows users to freely publish information regarding several subjects. Social content websites may take advantage of such by creating means for dissemination and creation of collaborative knowledge. However, an adequate environment is needed for the insertion of such information on social content websites. Mobile 2.0 incorporates some Web 2.0 concepts on mobile platforms using context-aware information captured from sensors, like GPS. This paper presents a model based on social content websites that uses context ontologies for the provision of personalized services on mobile platforms.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116134515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-12-01DOI: 10.1109/CASON.2011.6085927
P. Vojtás, J. Pokorný, M. Nečaský, T. Skopal, K. Matousek, Jiří Kubalík, Ota Novotný, Milos Maryska
This paper describes the concept of a social network of the ICT specialists in the regions of the Czech Republic. In particular, we focus on the web portal under development, i.e. a software tool serving for the network implementation. Associated activities concerning collecting and analyzing ICT requirements from companies and educational ICT knowledge of university graduates are presented. The novelty of our approach is in focusing on specificities of the social network (entities and relationships specific for ICT) and in the concept of professional profile (PP). Professional profiles enable to express the ICT focus of a given entity (e.g., person, research team or project) in a structured way. Based of the PP concept, we introduce specific portal functionalities which are not offered by existing portals.
{"title":"SoSIReČR - IT professional social network","authors":"P. Vojtás, J. Pokorný, M. Nečaský, T. Skopal, K. Matousek, Jiří Kubalík, Ota Novotný, Milos Maryska","doi":"10.1109/CASON.2011.6085927","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085927","url":null,"abstract":"This paper describes the concept of a social network of the ICT specialists in the regions of the Czech Republic. In particular, we focus on the web portal under development, i.e. a software tool serving for the network implementation. Associated activities concerning collecting and analyzing ICT requirements from companies and educational ICT knowledge of university graduates are presented. The novelty of our approach is in focusing on specificities of the social network (entities and relationships specific for ICT) and in the concept of professional profile (PP). Professional profiles enable to express the ICT focus of a given entity (e.g., person, research team or project) in a structured way. Based of the PP concept, we introduce specific portal functionalities which are not offered by existing portals.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126814118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-11DOI: 10.1109/CASON.2011.6085913
B. Arief, A. Moorsel, David Greathead, L. Coventry
In this paper we discuss the current state of our work regarding the development and planned in-situ testing of a computer-based system to enhance community relations through the Neighbourhood Watch scheme. The system is intended for use in a community to help the residents interact with each other more easily and to encourage the reporting of suspicious behaviour or crime. We discuss some details of the system and how we plan to test it in the field using an iterative process. We also discuss the possible implications of the work for the future.
{"title":"Towards the implementation of an internet-based neighbourhood watch scheme-Impacts of inclusive technologies on societies","authors":"B. Arief, A. Moorsel, David Greathead, L. Coventry","doi":"10.1109/CASON.2011.6085913","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085913","url":null,"abstract":"In this paper we discuss the current state of our work regarding the development and planned in-situ testing of a computer-based system to enhance community relations through the Neighbourhood Watch scheme. The system is intended for use in a community to help the residents interact with each other more easily and to encourage the reporting of suspicious behaviour or crime. We discuss some details of the system and how we plan to test it in the field using an iterative process. We also discuss the possible implications of the work for the future.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115167967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-01DOI: 10.1109/CASON.2011.6085951
Piotr Bródka, K. Skibicki, Przemyslaw Kazienko, Katarzyna Musial
Multi-layered social networks reflect complex relationships existing in modern interconnected IT systems. In such a network each pair of nodes may be linked by many edges that correspond to different communication or collaboration user activities. Multi-layered degree centrality for multi-layered social networks is presented in the paper. Experimental studies were carried out on data collected from the real Web 2.0 site. The multi-layered social network extracted from this data consists of ten distinct layers and the network analysis was performed for different degree centralities measures.
{"title":"A degree centrality in multi-layered social network","authors":"Piotr Bródka, K. Skibicki, Przemyslaw Kazienko, Katarzyna Musial","doi":"10.1109/CASON.2011.6085951","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085951","url":null,"abstract":"Multi-layered social networks reflect complex relationships existing in modern interconnected IT systems. In such a network each pair of nodes may be linked by many edges that correspond to different communication or collaboration user activities. Multi-layered degree centrality for multi-layered social networks is presented in the paper. Experimental studies were carried out on data collected from the real Web 2.0 site. The multi-layered social network extracted from this data consists of ten distinct layers and the network analysis was performed for different degree centralities measures.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128136818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-10-01DOI: 10.1109/CASON.2011.6085937
J. Cruz, Cécile Bothorel, F. Poulet
Social network analysis has become a major subject in recent times, bringing also several challenges in the computer science field. One aspect of the social network analysis is the community detection problem, which can be seen as a graph clustering problem. However, social networks are more than a graph, they have an interesting amount of information derived from its social aspect, such as profile information, content sharing and annotations, among others. Most of the community detection algorithms use only the structure of the network, i.e., the graph. In this paper we propose a new method which uses the semantic information along with the network structure in the community detection process. Thus, our method combines an algorithm for optimizing modularity and an entropy-based data clustering algorithm, which tries to find a partition with low entropy and keeping in mind the modularity.
{"title":"Entropy based community detection in augmented social networks","authors":"J. Cruz, Cécile Bothorel, F. Poulet","doi":"10.1109/CASON.2011.6085937","DOIUrl":"https://doi.org/10.1109/CASON.2011.6085937","url":null,"abstract":"Social network analysis has become a major subject in recent times, bringing also several challenges in the computer science field. One aspect of the social network analysis is the community detection problem, which can be seen as a graph clustering problem. However, social networks are more than a graph, they have an interesting amount of information derived from its social aspect, such as profile information, content sharing and annotations, among others. Most of the community detection algorithms use only the structure of the network, i.e., the graph. In this paper we propose a new method which uses the semantic information along with the network structure in the community detection process. Thus, our method combines an algorithm for optimizing modularity and an entropy-based data clustering algorithm, which tries to find a partition with low entropy and keeping in mind the modularity.","PeriodicalId":342597,"journal":{"name":"2011 International Conference on Computational Aspects of Social Networks (CASoN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130819013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：