scholarly journals Social: An Algorithmic Stable Coin for Social Influence

2021 ◽  
Author(s):  
Andrew Kamal
Keyword(s):  
Social Networks ◽  
Social Influence ◽  
Mathematical Models ◽  
Market Access ◽  
Smart Contracts ◽  
Process Data ◽  
Access Protocols ◽  
Social Physics ◽  
Access Data ◽  
Over Time

Social is an algorithmic stable coin for social influence, built off of UMA or Universal Market Access Protocols, CloutContracts (CCS), and on the Celo network. It is based off of quantitative algorithmic stabilization provided by a social coin's perceived cryptographic value. Social is a utility and this technology is conceptual. How Social works, is by integrating statistical averages for CCS and social tokens staked within its network. It integrates universal market access in regards to CCS data (CloutContracts is a smart contracts platform for social influencers and creators). Social as an algorithmically pegged stable coin, will eventually create a standard for social influence. Decentralized finance applications might even peg cryptographic value to Social as a utility. Social can integrate decentralized oracles in order to process data much quicker over time, once the network becomes large enough. Since CloutContracts integrates social networks across various different places such as DeSo/BitClout, Minds, Peepeth, Steemit, etc., one can eventually establish some sort of cryptographic metric in regards to social influence, and develop complex algorithms centered around social physics and human behavioral processes. The same type of mathematical models that apply to quantitative algorithms in the stock market for example, can apply to social influence. The same also applies for mathematical models modeled after games like chess and go. Social as a stable coin, creates another complexity that CloutContracts can use to create new mathematical standards around market access data that it already has, and could be quite critical. Social influence as a market, and as some sort of utility, can then be looked at as either a metric, mathematical bet, or speculative model for new forms of political and human societies.

scholarly journals Peer Attitudes and the Development of Prejudice in Adolescence

2018 ◽  
Vol 4 ◽  
pp. 237802311876318 ◽  
Author(s):  
Mikael Hjerm ◽  
Maureen A. Eger ◽  
Rickard Danell
Keyword(s):  
Social Networks ◽  
Social Context ◽  
Longitudinal Data ◽  
Social Influence ◽  
Social Environment ◽  
Network Centrality ◽  
Peer Attitudes ◽  
Data Limitations ◽  
The Relationship ◽  
Over Time

According to a number of psychological and sociological theories, individuals are susceptible to social influence from their immediate social environment, especially during adolescence. An important social context is the network of one’s peers. However, data limitations, specifically a lack of longitudinal data with information about respondents’ social networks, have limited previous analyses of the relationship between peers and prejudice over time. In this article, we rely on a five-wave panel of adolescents, aged either 13 or 16 in wave 1 (N = 1,009). We examine the effects of this social context on prejudice by focusing on nominated friends’ attitudes, attitudes of prestigious peers, and respondents’ own positions in their networks. Results indicate that the level of prejudice among peers affects individual prejudice over time. Results also show that both prestigious and nonprestigious peers affect prejudice. Finally, adolescents’ own positions in their networks matter: Network centrality is inversely related to prejudice.

Rethinking social remittances and the migration-development nexus from the perspective of time

2013 ◽  
Vol 10 (1) ◽  
pp. 11-22 ◽  
Author(s):  
Peggy Levitt ◽  
Deepak Lamba-Nieves
Keyword(s):  
Social Influence ◽  
Change Over Time ◽  
Social Remittances ◽  
The Relationship ◽  
Migration And Development ◽  
Over Time

This article explores how the conceptualization, management, and measurement of time affect the migration-development nexus. We focus on how social remittances transform the meaning and worth of time, thereby changing how these ideas and practices are accepted and valued and recalibrating the relationship between migration and development. Our data reveal the need to pay closer attention to how migration’s impacts shift over time in response to its changing significance, rhythms, and horizons. How does migrants’ social influence affect and change the needs, values, and mind-frames of non-migrants? How do the ways in which social remittances are constructed, perceived, and accepted change over time for their senders and receivers?

Market access, teff production, and fertilizer use over time

2018 ◽  
Author(s):  
International Food Policy Research Institute (IFPRI)
Keyword(s):  
Market Access ◽  
Fertilizer Use ◽  
Over Time

scholarly journals Challenging the Status Quo through Social Influence: Changes in Sustainable Consumption through the Influence of Social Networks

2021 ◽  
Vol 13 (10) ◽  
pp. 5513
Author(s):  
Iljana Schubert ◽  
Judith I. M. de Groot ◽  
Adrian C. Newton
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Influence ◽  
Food Consumption ◽  
Status Quo ◽  
Injunctive Norms ◽  
Sustainable Food ◽  
Consumption Choices ◽  
The Status ◽  
Consumption Practices

This study examines the influence of social network members (versus strangers) on sustainable food consumption choices to investigate how social influence can challenge the status quo in unsustainable consumption practices. We hypothesized that changes to individual consumption practices could be achieved by revealing ‘invisible’ descriptive and injunctive social norms. We further hypothesized that it matters who reveals these norms, meaning that social network members expressing their norms will have a stronger influence on other’s consumption choices than if these norms are expressed by strangers. We tested these hypotheses in a field experiment (N = 134), where participants discussed previous sustainable food consumption (revealing descriptive norms) and its importance (revealing injunctive norms) with either a stranger or social network member. We measured actual sustainable food consumption through the extent to which participants chose organic over non-organic consumables during the debrief. Findings showed that revealed injunctive norms significantly influenced food consumption, more so than revealed descriptive norms. We also found that this influence was stronger for social network members compared to strangers. Implications and further research directions in relation to how social networks can be used to evoke sustainable social change are discussed.

scholarly journals An Exploratory Study of COVID-19 Information on Twitter in the Greater Region

2021 ◽  
Vol 5 (1) ◽  
pp. 5
Author(s):  
Ninghan Chen ◽  
Zhiqiang Zhong ◽  
Jun Pang
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Online Social Networks ◽  
Exploratory Study ◽  
Representation Learning ◽  
Data Driven ◽  
Learning Methods ◽  
Twitter Users ◽  
Over Time

The outbreak of the COVID-19 led to a burst of information in major online social networks (OSNs). Facing this constantly changing situation, OSNs have become an essential platform for people expressing opinions and seeking up-to-the-minute information. Thus, discussions on OSNs may become a reflection of reality. This paper aims to figure out how Twitter users in the Greater Region (GR) and related countries react differently over time through conducting a data-driven exploratory study of COVID-19 information using machine learning and representation learning methods. We find that tweet volume and COVID-19 cases in GR and related countries are correlated, but this correlation only exists in a particular period of the pandemic. Moreover, we plot the changing of topics in each country and region from 22 January 2020 to 5 June 2020, figuring out the main differences between GR and related countries.

Decomposition of Growth Curves into Growth Rate and Acceleration: a Novel Procedure to Monitor Bacterial Growth and the Time-Dependent Effect of Antimicrobials

2021 ◽  
Author(s):  
M. Luisa Navarro-Pérez ◽  
M. Coronada Fernández-Calderón ◽  
Virginia Vadillo-Rodríguez
Keyword(s):  
Growth Rate ◽  
Mathematical Models ◽  
Bacterial Growth ◽  
Time Course ◽  
Antimicrobial Agents ◽  
Numerical Procedure ◽  
Growth Curves ◽  
Predictive Microbiology ◽  
Insight Into ◽  
Over Time

In this paper, a simple numerical procedure is presented to monitor the growth of Streptococcus sanguinis over time in the absence and presence of propolis, a natural antimicrobial. In particular, it is shown that the real-time decomposition of growth curves obtained through optical density measurements into growth rate and acceleration can be a powerful tool to precisely assess a large range of key parameters [ i.e. lag time ( t 0 ), starting growth rate ( γ 0 ), initial acceleration of the growth ( a 0 ), maximum growth rate ( γ max ), maximum acceleration ( a max ) and deceleration ( a min ) of the growth and the total number of cells at the beginning of the saturation phase ( N s )] that can be readily used to fully describe growth over time. Consequently, the procedure presented provides precise data of the time course of the different growth phases and features, which is expected to be relevant, for instance, to thoroughly evaluate the effect of new antimicrobial agents. It further provides insight into predictive microbiology, likely having important implications to assumptions adopted in mathematical models to predict the progress of bacterial growth. Importance: The new and simple numerical procedure presented in this paper to analyze bacterial growth will possibly allow identifying true differences in efficacy among antimicrobial drugs for their applications in human health, food security, and environment, among others. It further provides insight into predictive microbiology, likely helping in the development of proper mathematical models to predict the course of bacterial growth under diverse circumstances.

scholarly journals On attracting sets in artificial networks: cross activation

2018 ◽  
Vol 16 ◽  
pp. 01005
Author(s):  
Felix Sadyrbaev
Keyword(s):  
Dynamical Systems ◽  
Differential Equations ◽  
Mathematical Models ◽  
Ordinary Differential Equations ◽  
Critical Points ◽  
Regulatory Networks ◽  
Main Diagonal ◽  
Sigmoidal Function ◽  
Genomic Regulatory Networks ◽  
Over Time

Mathematical models of artificial networks can be formulated in terms of dynamical systems describing the behaviour of a network over time. The interrelation between nodes (elements) of a network is encoded in the regulatory matrix. We consider a system of ordinary differential equations that describes in particular also genomic regulatory networks (GRN) and contains a sigmoidal function. The results are presented on attractors of such systems for a particular case of cross activation. The regulatory matrix is then of particular form consisting of unit entries everywhere except the main diagonal. We show that such a system can have not more than three critical points. At least n–1 eigenvalues corresponding to any of the critical points are negative. An example for a particular choice of sigmoidal function is considered.

Cracks in the Network Conversion Paradigm

2012 ◽  
Vol 3 (2) ◽  
pp. 143-162 ◽  
Author(s):  
James Lewis
Keyword(s):  
Social Networks ◽  
Change Over Time ◽  
New Religions ◽  
Dominant Point ◽  
Recruitment Patterns ◽  
Over Time

One of the standard generalizations about new religions is that people convert to NRMs primarily through preexisting social networks. The present paper examines data on a variety of new religions which demonstrates that social networks are not always the dominant point of contact for new converts. Additionally, recruitment patterns change over time so that different factors become dominant at different points in a movement’s development. Two reasons why this variability has escaped the attention of most researchers is an unconscious tendency to assume that the sociological profiles of members of different NRMs are essentially similar, and the fact that such groups are typically studied synchronically rather than diachronically.

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