Online Social Networks and Media (OSNEM) are one of the most disruptive  communication platforms of the last 15 years with high socio-economic value.
Within this framework, the network properties of OSNEM can be used to capture multiple phenomena related to OSNEM, at different logical layers, from a technical perspective (e.g., OSNEM data management and information diffusion), as well as a societal perspective (e.g., the OSNEM users’ social structures). Moreover, the analysis of network dynamics represents one of the biggest challenges that emerged in recent years within the network science community.

Therefore, OSNeD will focus on the analysis of OSNEM from the standpoint of its network properties and dynamics at all scales, from macro- to meso- (e.g., community) to micro (e.g., ego network) scales. It will be particularly interesting to highlight the impact of network properties and dynamics on emerging phenomenon, such as diffusion of information, the acquisition of the role of influencer, trust among users, polarization of opinions, diffusion of fake news, etc.

The OSNeD workshop aims at engaging a multidisciplinary community.
The workshop also welcomes submissions applying a wide range of (computer- and network-science) techniques and tools to OSNEM for investigating the properties and roles of the network of (online) social relationships in the various sectors of the society (e.g., politics, economics, finance, health, entertainment).

Topics

Within the general focus of the workshop on OSNEM network properties and dynamics, topics include:

• OSNEM platforms, protocols and applications;
• Decentralized, mobile and location-based OSNEM;
• Dynamic Analysis of OSNEM
• Trust, reputation, privacy and security in OSNEM;
• Recommendations and advertising in OSNEM;
• Measurement, analysis and modeling of popular OSNEM platforms (Facebook,
  Twitter, Instagram, Flickr, etc.);
• BigData analysis of OSNEM seen as large- meso- or micro-scale complex
  networked systems;
• Information extraction and search in OSNEM;
• Complex-network analysis of OSNEM;
• Measurement, analysis and modeling of social networked users’ behavior through OSNEM data;
• Analysis of the use of OSNEM in the urban context;
• Network challenges of crowdsourcing is OSNEM;
• Network challenges in multidisciplinary applications of OSNEM (economics,
  medicine, society, politics, homeland security, etc.)
• OSNEM event detection;
• Evolutionary community / cluster discovery;
• Dynamic network generative models;
• Dynamic network embedding;
• Dynamics of trends, information and opinion diffusion in OSNEM