Chrono-spatial intelligence in global systems science and social media: Predictions for proactive political decision making

Abstract

This paper discusses the advantage of social media in providing continuous non-liner, non-redundant information, taking advantage Global Systems Science (GSS) research tools and techniques. GSS matrix can indicate series of fortunate and unfortunate events that are not isolated but rather connected in time and space, sometimes appearing as events rising from serendipity. This proposition suggests that such hidden connections can be a new form of multiple intelligence named Chrono-Spatial Intelligence This is occurring by apparent or hidden connections between human or machine generated data and the time these occur so to investigate their connecting nodes, also linked to political decision making and learning. Although major prediction frameworks and systems exist as part of the GSS, it seems they cannot not successfully indicate or predict major or massive activities with global impact following the latest global events. Social media, semantic associations, local security camera data and other information have not been connected and analysed enough to predict undesirable events. Therefore, the main aim of this proposition is the identification, analysis and understanding connections between real-time political events for time-space investigation as Chrono-Spatial Intelligence. A second aim is to identify tools, methodologies and evaluation techniques to facilitate shedding light in Chrono- Spatial Intelligence understanding, analysis and impact related to political decision making, as for example quality in education. Future research suggests the proposition implementation.