SSNN 2019 - 1st International Symposium on Social Issues analysis and visualisation in Online Social Networks

Social issues in Online Social Networks (SSNN) have attracted the general interest, in part due to the broad usage of SSNN among people, organizations and companies as well as to the political climate of the world. The analysis and visualization of how SSNN are used by different people, communities and groups can provide useful insights on social practices, behaviours and needs that can be used for varied purposes. There are also many social concerns about the use of SSNN that can be faced using network analysis and visualization techniques, including information reliability, transparency, privacy issues, fraud detection, fake news propagation, or digital divides. The information in SSNN is heterogeneous, unstructured and spontaneously generated, but if it is made available in an interpretable and accurate way to decision makers the right actions can be undertaken. Well-designed analysis and visualization tools will allow also to understand better the real impact of SSNN and how they can be used to improve communication with users and communities, with social, cultural or economic purposes, or even to strengthen the social capital and make communities more resilient.
Within this context, contributions to this symposium are expected to deal with case studies, algorithms, analytic and visualization tools, methods and techniques that address topics such as:
Social issues related with the use of SSNN (including economic, cultural or gender biases)
SSNN activity and behaviors in specific contexts (online advertising, politics, crisis, …)
SSNN usage in specific communities (such as elder, immigrants, vulnerable communities and groups…)
Detection and prevention of fraud and fake news propagation
SSNN data quality, privacy and transparency
Methods and techniques to support decision making and situational awareness based on SSNN data
Impact of SSNN on the community social capital
Uses of SSNN to improve social interaction
Integration of SSNN data with other back-channel and official sources of information
Intelligent techniques to mine and visualize data
Program Committee
Andres Abeliuk, University of Southern California, USA
Sotirios Chatzis, Cyprus University of Technology, CY
Herodotos Herodotou, Cyprus University of Technology, CY
Kaj Kolja Kleineberg, ETH, Zurich, CH
Steffen Lohmann . Fraunhofer IAIS / Universität Bonn (EIS), DE
Alan MacEachren. Penn State University, USA
Teresa Onorati. Universidad Carlos III de Madrid, ES
Anxo Sánchez. Universidad Carlos III de Madrid, ES
Monica Sebillo. Università degli Studi di Salerno, IT
Michael Sirivianos, Cyprus University of Technology, Cyprus
Giuliana Vitiello. Università degli Studi di Salerno, IT