The quintessence of networking has always been that individuals or organizations have used their direct and indirect contacts to mobilize support, to share ideas, or to sell products and services. In the meantime, a series of specialized methods have been developed to collect and analyze such egocentric network data.
These methods will be the focus of the upcoming summer school Polnet Plus, which this year will be jointly organized by Ulrik Brandes (ETH Zurich) and Volker Schneider (University of Konstanz) at the University of Konstanz at July 6 and 7, 2018.
The summer school includes a keynote speech by José Luis Molina (Universitat Autònoma de Barcelona), various sessions that introduce the participants into the topic, the collection of egocentric network data with VennMaker, the visualization of such data in visone, and the basics of ego-network data analysis in R.
The Workshop will be held on Friday, August 31, 2018, in Rio de Janeiro, Brazil.
Topics of interest include, but are not limited to:
- Data mining of social data for urban planning
- Social data analytics for city evaluation
- Social data integration or fusion
- Social IoT
- Knowledge integration
- Social, Knowledge and Big Data integration
- Urban and city dynamics sensoring
- Crowd dynamics at large scale of events
- Big social data applied to neglected populations
- Traffic and human mobility
- Big social data modeling, visualization, analysis, and prediction
- Urban economics based on social data
- Social behavior modeling, understanding, and patterns mining in urban spaces
- Ethical issues in social data analysis
- Public safety, security, and privacy in urban sensing
- Semantics for big social data
- Visualization of city-wide social data in urban areas
- Smart recommendations in urban spaces
- Mining data from the internet of things in urban areas
- Managing urban big social data in the cloud
- Big social data and IoT frameworks and infrastructures
- Smart city open data
- Ubiquitous/pervasive intelligent social systems in urban areas
- Understanding urban economy based on big social data
- Location-based social networks enabling urban computing scenarios
- Intelligent delivery services in cities
- Influences from the real physical world on social data, and viceversa +