***** To join INSNA, visit http://www.insna.org ***** *-- Apologies for cross-posting --* Dear colleagues, Please consider submitting a contribution to the "Complex Systems for the Most Vulnerable - 2nd Edition" satellite workshop ( https://urldefense.proofpoint.com/v2/url?u=https-3A__cs4v19.weebly.com_&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=gxAmIMD6Sl-je9rlAXi-3egrlf2SGr8WpdZLvl3fkIk&s=ToVzv3CWEvTeOb7zV4PoVn1AAaw1qxYXwoLB-tkSC4w&e= ), that will take place at CCS2019 in Singapore on October 3rd, 2019. Data and data science are becoming more and more crucial to meeting the societal challenges that climate change, ever increasing inequalities, geopolitical upheaval etc are creating. The need for a new scientific approach to social innovation, international development and humanitarian aid has never been clearer. In this context, the role that Complex Systems can play is central and crucial. On one hand, they can provide a robust theoretical framework to address issues such as replicability and transferability of work with a focus on vulnerable contexts, as well as explainability of models and challenges of data biases. On the other hand, the applied nature of several branches of Complex Systems can help in identifying the ideal areas of applications (e.g. epidemics) that can result in the highest scientific impact. This Workshop has the goal of reviewing the potential effective contributions that Complex Systems can have on creating public value and producing public policy practices that can be applied in vulnerable contexts. It aims both at showcasing the most relevant work produced by the Complex Systems community in this area, and at focusing the attention of this scientific community on the pressing issues that affect the most vulnerable populations. Topics of interest will be (but are not limited to): - Replicability and transferability of models in vulnerable and data-poor contexts - Data representativeness and bias and algorithmic privacy, transparency and fairness in the context of social good applications - Models interpretability in support of better decision making - Complex systems applied to impact measurement of social good programs - Emergence and dynamics of vulnerability and inequalities (e.g. tipping points for poverty; scaling dynamics; second order effects...) Areas of applications can be (but are not limited to): - Gender bias and data gaps - Health in developing countries - Migrations and xenophobia - Education - Unemployment - Inequalities and poverty reduction - Environment and sustainability This year's invited speakers will be: - Prof. Samuel V. Scarpino (Network Science Institute at Northeastern University | ISI Foundation Fellow | Chief Strategy Officer at Dharma Platform) - Prof. Claudia Wagner (Interim Director of Computational Social Science Department, GESIS - Leibniz Institute for Social Sciences | W1 Professor for Data Science at University Koblenz-Landau) - Prof. Saini Yang (Beijing Normal University | Director, International Center for Collaborative Research on Disaster Risk Reduction) Please submit your abstract via the EasyChair website: *https://urldefense.proofpoint.com/v2/url?u=https-3A__easychair.org_conferences_-3Fconf-3Dcs4v&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=gxAmIMD6Sl-je9rlAXi-3egrlf2SGr8WpdZLvl3fkIk&s=n9O1MIdaM9YO2q73mv0N7sxkvpVX3k04fOF8PHdQ1DA&e= <https://urldefense.proofpoint.com/v2/url?u=https-3A__easychair.org_conferences_-3Fconf-3Dcs4v&d=DwIBaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=gxAmIMD6Sl-je9rlAXi-3egrlf2SGr8WpdZLvl3fkIk&s=n9O1MIdaM9YO2q73mv0N7sxkvpVX3k04fOF8PHdQ1DA&e= >* . Submissions should be at most two pages long and include the following information: title of the talk, author(s), affiliation(s), e-mail address(es), abstract and one or two figures. *Abstract submission deadline is June 30th, 2019*. Authors of accepted abstracts will be notified by e-mail no later than July 10th 2019. Best regards, CS4V19 Organizing Committee _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.