2020 Ieee Acm International Conference On Advances In Social Networks Analysis And Mining Asonam

Social network analysis and mining

The conference solicits experimental and theoretical works on social network analysis and mining along with their application to real life situations

The conference solicits experimental and theoretical works on social network analysis and mining along with their application to real life situations

The international conference on Advances in Social Network Analysis and Mining (ASONAM 2015) will primarily provide an interdisciplinary venue that will bring together practitioners and researchers from a variety of SNAM fields to promote collaborations and exchange of ideas and practices ASONAM 2015 is intended to address important aspects with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining The conference solicits experimental and theoretical works on social network analysis and mining along with their application to real life situations

The conference will consider papers in all areas of social networks and mining In recent years, social network research has advanced significantly the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution This has led to a rising prominence of SNAM in academia, politics, homeland security and business This follows the pattern of known entities of our society that have evolved into networks in which actors are increasingly dependent on their structural embedding

The international conference series on Advances in Social Network Analysis and Mining (ASONAM 2022) provides an interdisciplinary venue that brings together researchers and practitioners from a broad variety of fields to promote collaborations and exchange of ideas and practices ASONAM 2022 is intended to address important aspects with a specific focus on emerging trends and industry needs The conference solicits empirical, experimental, methodological, and theoretical research reporting original and unpublished results on social network analysis and mining along with applications

The IEEE ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM) provides a premier interdisciplinary forum to bring together researchers and practitioners from all social networking analysis and mining related fields for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences ASONAM 2014 seeks to address important challenging problems with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining The conference solicits experimental and theoretical findings along with their real world applications General areas of interest to ASONAM 2014 include the design, analysis and implementation of social networking theory, systems and applications from computer science, mathematics, communications, business administration, sociology, psychology, anthropology, applied linguistics, biology and medicine

This book examines modern paradigms of disease control based on social network surveillance applications, including electronic sentinel surveillance and wireless application-based surveillance science. It also highlights topics that integrate statistical and epidemiological sciences with surveillance practice and, in order to reflect the evolution of social networking practices, discusses topics concerning the challenges for surveillance theory and practice. In turn, the book goes a step further by providing insights on how we need to analyse epidemiological trends by following best practices on distinguishing useful information from noise, namely fake news, false reporting of disease incidents and events, etc. At the same time, we need to be able to protect health-focused applications and communication tools via cybersecurity technologies and to ensure that anonymity of reporting and privacy are preserved. In closing, the book discusses the role and impact of social media on disease surveillance, as well as the current role of communities in infectious disease surveillance and control.