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This paper aims to initiate a new, formal theory of sociocultural physics.

Its intended scope is limited to predicting either long‐term, large‐scale or short‐term, small‐scale sociocultural events. The theory that the authors develop, called sociohistory, links three independent but relatable approaches: part of Sorokin's epistemological theory of sociocultural dynamics, Frieden's epistemological theory of extreme physical information (EPI), and Yolles's social viable systems (SVS) theory.

Although not all of Sorokin's ideas are universally accepted, a subset of them is found to be extremely useful for describing the conceptual context of complex systems. This includes how sociocultural processes link closely into political processes.

The theory that develops helps explain how opposing, cultural enantiomers or yin‐yang forces (represented, for instance, by the polar mindsets represented in Islamic fundamentalism and global enterprise) can result in violent conflict, or in either viable or non‐viable social communities. The informations I and J of EPI theory are regarded, respectively, as sensate and ideational enantiomers.

While the resulting sociocultural physics is in its infancy, an illustrative application to the developmental dynamics of post‐colonial Iran demonstrates its potential utility.

Academic social networking (ASN) sites are becoming a popular communication medium among scholars. This case study was designed to explore communication behaviors of physicists, linguists, and sociologists on an ASN site called Academia.edu, their motivations for using it, and the perceived impact of their use of the site on their professional activities. Results from this study are valuable for designing computer-mediated and web-based communication media for scholars and also for adding richness to the literature related to scholarly communication. For the purpose of this study, data was collected using three different instruments: Server log, survey, and interview. Data used for analyses included a total of 20,309 server log data, 267 survey responses, and 28 interviews from scholars of Physics, Sociology, and Linguistics who use Academia.edu. Results from the study showed that the use of Academia.edu is dependent on the discipline scholars are affiliated with, their professional status, and the time of the year. Unlike physicists, linguists and sociologists are more inclined to using Academia.edu and other ASN sites. Although linguists and sociologists actively use Academia.edu, their motivations to use the site are different. These differences in user-motivations and user-activities across the disciplines are influenced by variations in the social and cultural practices of the disciplines. This study used Whitley’s (2000) theory of degrees of mutual dependence and task uncertainty to explain the differences in the adoption and use of Academia.edu across the three disciplines.

Internet-based intangible network good (IING) has revolutionized multiple industries in recent years. This paper aims to reveal the laws of consumer’s decision-making on IING from a perspective of kinetic energy and potential energy.

In this paper, 4 aspects and 17 factors influencing IING adoption were generalized. Based on the theory of social physics, an agent-based simulation model, introducing physical energy theory to depict consumer’s decision-making, was built. An agent’s kinetic energy reflects the agent’s perceived effect of mass media on the agent’s decision-making on IING adoption. An agent’s potential energy reflects the agent’s perceived effect of social interactions on the agent’s decision-making on the adoption of IING. An agent’s final energy is the sum of the kinetic energy and potential energy, which reflects the agent’s final decision.

Some factors mainly influence the diffusion velocity, while other factors have a dramatic impact on both diffusion velocity and diffusion scale. The agent’s personality can make a difference at the early and middle stages of IING adoption, but a faint impact at the later stage because of the effects of network externalities and word of mouth. There is a critical value of the number of initial adopters which can dramatically speed up IING adoption.

This study provides new insights for firms on the effects of factors influencing consumers’ decision-making on IING adoption.

This paper defines a new kind of innovation, IING, and generalizes IING’s special characteristics. As a new application of social physics, the physical energy theory has been creatively introduced to depict consumer’s decision-making on IING adoption. A kinetic and potential energy model of IING adoption has been built. Based on simulation experiments, new insights of IING adoption have been gained.

Perhaps the greatest peril to civilisation is the fragmentation of knowledge. Science often lends itself to easy application to technology and our economic systems are the result of applying this knowledge to our resources. But our knowledge of how societies work lags significantly, and the economic system frequently multiplies our social problems. At the heart of the problem is the distinction between knowledge of universals – scientific laws for example – and knowledge of people, who are unique particulars. The paper examines some recent disputes in the social sciences and suggests how the gap might be filled and economic systems made more responsive to social problems.

Internet-based intangible network good (IING) has undergone rapid developments, even revolutionized multiple industries in recent years. IING is highly dependent on the rapid diffusion rates for development success. For firms, how to select the initial targets or “seeding points” to accelerate the adoption process is critical in network marketing campaigns. The purpose of this study is to provide a new method to identify the optimal initial adopters and adoption paths.

First, the author generalize three aspects influencing IING’s adoption, namely, innovation attributes, customer’s personality and word-of-mouth. Next, we establish a modified gravity model to describe how social interactions affect consumer’s adoption behavior. Then, simulate the adoption process by setting each agent as the initial adopter to identify the optimal initial adopters. Finally, trace the information flow to forecast the adoption paths.

The model reveals how individual interactions (micro level) aggregate into the diffusion process (macro level). The optimal initial adopters are determined by a combination of factors as follows: IING’s attributes, the adopter’s diffusion ability, the potential-adopter’s personality and the trust degree between adopters and potential-adopters. Among all these factors, trust degree plays a most important role.

This study proposes the conceptual model of IING’s adoption from a perspective of dyadic influence, in which an adopter’s influence on its peers depends on pairwise characteristics of both parties. The authors propose a new method to identify the optimal initial adopters and adoption paths based on the gravity model. It is the first time to introduce the gravity model to describe IING’s adoption, which is a creative application of social physics. The findings provide new insights in IING’s adoption and identifying the key nodes in networks.

The purpose of this paper is to show that virtual mirroring-based learning allows members of an organization to see how they communicate with others in a visual way, by applying principles of “social quantum physics” (empathy, entanglement, reflect, reboot), to become better communicators and build a shared “DNA” within their organization.

E-mail based social network analysis creates virtual maps of communication – social landscapes – of organizations, similar to Google Maps, which creates geographical maps of a person’s surroundings.

Applying virtual mirroring-based learning at various mulitnational firms has significantly increased their organizational efficiency and performance, for instance increasing customer satisfaction by 18 per cent in a large services organization, increasing retention, making sales forecasts, and improving call center employee satisfaction.

To address concerns of individual privacy, the guiding principle is to give individual information to the individual and provide aggregated anonymized information to management.

Virtual mirroring-based learning offers a unique way of creating collective awareness within an organization by empowering the individual to take corrective action aligned with collective action, and improves their own communication behavior through analyzing and visualizing their e-mail archive in novel ways, while giving strategic insight to management and improving organizational culture.

The purpose of this paper is to advance clarity and precision around effective action in networks, understood as collaboration that: first, deepens the learning and engagement of students and adults; second, enhances the professional capital of teachers and leaders; and third, becomes a positive force of whole system improvement. It distills eight essential features of effective networks by fleshing out key lessons from existing research and from emerging education network developments in the English-speaking world and Latin America. It then discusses three shifts required for a new partnership between networks and central leadership to turn networks into forces of educational system renewal.

Two sources of evidence were identified and reviewed: first, literature reviews and studies aimed at identifying characteristics of effective networks in education; and second, network case studies and R & D initiatives that used networks as their improvement strategy and had demonstrated positive impact on student outcomes or on one or more professional capital variables often associated with improved student outcomes. To distill the eight essential features of effective networks and three required shifts in the relationship between networks and central leadership, the authors engaged in an iterative process of thematic analysis (Boyatzis, 1998) deliberately searching for key characteristics and processes describing effective collaboration. The list was revised for completeness and parsimony.

The eight essential features of effective networks identified are: first, focussing on ambitious student learning outcomes linked to effective pedagogy; second, developing strong relationships of trust and internal accountability; third, continuously improving practice and systems through cycles of collaborative inquiry; fourth, using deliberate leadership and skilled facilitation within flat power structures; fifth, frequently interacting and learning inwards; sixth, connecting outwards to learn from others; seventh, forming new partnership among students, teachers, families, and communities; and eighth, securing adequate resources to sustain the work. The three required shifts in the relationship between networks and central leadership are: first, from supply driven to demand driven; second, from compliance oriented to learning oriented; and third, from bureaucracy to movement.

The key limitation derives from the scarce available evidence to date causally – or even co-relationally – connecting network activities with improved student learning. This paper summarizes what is known to date about effective collaboration in networks and advance a theory of action that causally links network activities with improved student outcomes and enhanced professional capital. This theory of action, summarized in eight essential features, simultaneously offers key hypotheses for social network theory in education and actionable guidelines to develop effective networks.

The eight essential features of effective networks and the three required shifts in the relationship between networks and central leadership presented here were intentionally framed as action oriented. They offer a clear and actionable set of guidelines to develop effective networks.

The power of networks as vehicles to dramatically improve schools and entire educational systems is yet to be realized. This paper offers guidelines to enhance the effectiveness of networks, and thus contributes to the realization of the yet unfulfilled promise of networks.

This work adds originality and value in three ways: first, it draws from both existing studies on effective networks and successful and promising education networks; second, its findings apply to multiple configurations of networks, across multiple contexts – existing publications place their focus on specific network configurations or a specific network case or initiative; third, it looks at effective collaboration in networks from the dual perspective of local problem solving and whole system improvement.