![[photo-1512573314-17727dcdf45c.jpg]] Photo by [Craig Whitehead](https://unsplash.com/@sixstreetunder?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) on [Unsplash](https://unsplash.com/photos/GMSlf2w-w3U?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) The SPHERES specify Crowdsourcing as a Collaborative revolution enabled by Cloud Computing with participation on massive scale as a key element, driven by “Self-Actualization” motivation. Crowdsourcing’s learning curve is creating interconnected super communities with ultimate labor abstraction and Freemium models supported by existing and new markets. We are at the edge or “Crowd/Community companies” era, **renting “Crowd Power”**, utilizing Cloud computing, promoting new trends and their community leaders, reshaping world as we know it today by affecting inter-social interpolation. Fundamentally, each community leads to a higher evolution of people / member interactions, however the major enabler for community creation are group leaders as depicted below. ![[Pasted image 20230709111940.png|Figure 1: Creation of Community]] Community network evolution stages are: 1. Member Concentration – personal connections , sharing individual goals and interests 2. Leader Profiling – Emergent Leadership exposed by knowledge, personality, number of connections, charisma or any other positive characteristics 3. Group concentration on Leader – center of focus and connections, leaders growing influence shape the group around him/her and gain power as a social entity 4. Community Emerging – is a step when there are more groups with similar characteristics and they started to fill empty space between them (growing number of members) 5. Group Networking – is executed by creation of numerous connections and social interactions between members and leaders from different groups 6. Community Network – represents high density of networked groups , often sharing same ideas and community goals, supported by higher level of community leaders Generally speaking, crowd follows leaders in order to acquire self-Actualization by creation of communities, which allows communication, sharing information and collaboration on global community tasks and goals. ![[Pasted image 20230709112005.png|Figure 2: Conceptual Community Structure]] Overall (picture above), the circle represents an encapsulation in all structures (group, community, network) and it’s a natural border between elements / structures inside and entities outside (same philosophy is applied across all systems at SPHERES). The communities are building blocks of Social Networks acting as an essential element of Crowdsourcing Idea. Community and Group borders are areas with instant “**Social Noise**” created by Weak connections, short-term social or cultural trends or significant social changes (such as creation, declining or structural changes) inside social structures (new leader, new community, group merge, etc.). ## Community types There are three different types of communities: Local, Global, and Virtual. Communities connected to physical world (Local and Global) can be mixed or act independently inside digital world (Virtual): - Local – Local Communities are focused on local issues such as anti-social behavior, economic development, local environment, community planning, regeneration, conservation, community safety and transport and highway issues. The Community is able to take on a variety of levels of responsibility for some local services, such as street cleaning, grass cutting, weed control or the maintenance of public conveniences. - Global – Global Communities are focused on global problems such as social and economic justice, environmental integrity, overall civilization issues and more. - Virtual – Virtual Communities are independent from physical world although they solve issues in the real world. Virtual Communities are essentially faster in communication and problem solving areas; however they are often over-connected (virtualized and multiplied connection between entities). ## Communities and Networks There is surprisingly a substantial distinction between human and machine networks, which is characterized by the connections and their structures. In Machine Networks, Connection and Structures have visible and stabile patterns, which is not always true for human networks. Human Networks are more dynamic, organic and overall unpredictable as a complex systems, although we can trace **Emergent Patterns** as prediction tool for incoming changes with high level complexity. Emergent patterns are clearly recognizable by: - Visible with significantly higher density of communication - Massive creation of new structures and connections - Emerging new networks and their evolution into new virtual entities with potential impact on existing networks and their communities It’s essentially a living organism influenced by external and/or internal elements and their actions. ![[Pasted image 20230709112045.png|Figure 3: Communities and Networks]] The Conceptual picture "World of Networks" depicted above, shows existing and new Networks with their communities and their potential roles in Crowdsourcing: - Social Network: Free Brains, Testers, Consumers - Academic Network: Innovators, Educators, Scientist - Business Network: Developers, Architects, Managers - Governance Network: Local Governance, Global Governance - Industry Network: Industries, Standards, Open Innovation - IOT & SOS Networks – Internet of Things and System of Systems: Machine, Sensors, Collective Intelligence To measure social relationships for social network predictions, we have to use relevant applicable method. Sociometry is a quantitative method for measuring social relationships, developed by psychotherapist Jacob L. Moreno. This method brings an innovative approach to sociology, which allows us to measure two types of sociometry (research and applied): - Research sociometry is focused on network explorations, concerned with relational patterns in small (individual and small group) and larger populations, such as organizations and neighborhoods. - Applied sociometry utilize a range of methods to assist people and groups review, expand and develop their existing psycho-social networks of relationships These two sociometry method can help in large scale to manage Social Networks and help to monetize them for Crowdsourcing purposes. The Social Network Analysis method emerged from Sociometry shows different approach in relationship measurement. The power of social network analysis stems from its difference from traditional social scientific studies, which assume that it is the attributes of individual actors—whether they are friendly or unfriendly, smart or dumb, etc.—that matter. Social network analysis produces an alternate view, where the attributes of individuals are less important than their relationships and ties with other actors within the network. This approach has turned out to be useful for explaining many real-world phenomena, but leaves less room for individual agency, the ability for individuals to influence their success, because so much of it rests within the structure of their network [1]. ## References [1] WIKIPEDIA: DEFINITIONS ## Related to [[SPHERES and Social Management - Introduction]]