Redefining the Market Power of Small-Scale Electricity Consumers through Consumer Social Networks

Author(s):  
Kyriakos C. Chatzidimitriou ◽  
Kostantinos N. Vavliakis ◽  
Andreas L. Symeonidis ◽  
Pericles A. Mitkas
2020 ◽  
Vol 39 (4) ◽  
pp. 5253-5262
Author(s):  
Xiaoxian Zhang ◽  
Jianpei Zhang ◽  
Jing Yang

The problems caused by network dimension disasters and computational complexity have become an important issue to be solved in the field of social network research. The existing methods for network feature learning are mostly based on static and small-scale assumptions, and there is no modified learning for the unique attributes of social networks. Therefore, existing learning methods cannot adapt to the dynamic and large-scale of current social networks. Even super large scale and other features. This paper mainly studies the feature representation learning of large-scale dynamic social network structure. In this paper, the positive and negative damping sampling of network nodes in different classes is carried out, and the dynamic feature learning method for newly added nodes is constructed, which makes the model feasible for the extraction of structural features of large-scale social networks in the process of dynamic change. The obtained node feature representation has better dynamic robustness. By selecting the real datasets of three large-scale dynamic social networks and the experiments of dynamic link prediction in social networks, it is found that DNPS has achieved a large performance improvement over the benchmark model in terms of prediction accuracy and time efficiency. When the α value is around 0.7, the model effect is optimal.


2016 ◽  
Vol 43 (3) ◽  
pp. 342-355 ◽  
Author(s):  
Liyuan Sun ◽  
Yadong Zhou ◽  
Xiaohong Guan

Understanding information propagation in online social networks is important in many practical applications and is of great interest to many researchers. The challenge with the existing propagation models lies in the requirement of complete network structure, topic-dependent model parameters and topic isolated spread assumption, etc. In this paper, we study the characteristics of multi-topic information propagation based on the data collected from Sina Weibo, one of the most popular microblogging services in China. We find that the daily total amount of user resources is finite and users’ attention transfers from one topic to another. This shows evidence on the competitions between multiple dynamical topics. According to these empirical observations, we develop a competition-based multi-topic information propagation model without social network structure. This model is built based on general mechanisms of resource competitions, i.e. attracting and distracting users’ attention, and considers the interactions of multiple topics. Simulation results show that the model can effectively produce topics with temporal popularity similar to the real data. The impact of model parameters is also analysed. It is found that topic arrival rate reflects the strength of competitions, and topic fitness is significant in modelling the small scale topic propagation.


Marine Policy ◽  
2017 ◽  
Vol 81 ◽  
pp. 340-349 ◽  
Author(s):  
Isidro Maya-Jariego ◽  
José F. Querevalú-Miñán ◽  
Lourdes G. Varela ◽  
Javier Ávila

2008 ◽  
Vol 7 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Prak Sereyvath ◽  
Kyoko Kusakabe ◽  
Ubolratana Suntornratana ◽  
Napaporn Sriputinibondh

AbstractThe study examined how the commodity chain of freshwater fresh fish trade between Thailand and Cambodia developed and became sex segregated, and how women small-scale traders are positioned in the chain. The open border policy increased trade and demand for fish, and made it more difficult for small-scale traders to secure fish. Lack of state control led to rent-seeking, which further closed opportunities for resourceless small-scale traders. Women small-scale border traders tried to counter the marginalization through establishing social networks, but with limited success. Field interviews with 86 traders at the border areas of Thailand and Cambodia were conducted to explore these points.


2018 ◽  
Vol 65 (4) ◽  
pp. 394-406 ◽  
Author(s):  
David Best ◽  
Amy Musgrove ◽  
Lauren Hall

It has long been recognised that changes in social networks (and the underpinning changes in personal and social identity) are strong predictors of both desistance from crime and recovery from substance use. Building on existing work attempting to measure and shift social networks and transitions to prosocial groups, the current study provides pilot data from prisoners and family members about a visualisation technique widely used in specialist addiction treatment (node-link mapping) to map opportunities for linkage to prosocial groups and networks. The data presented in the paper are from a small-scale feasibility pilot. This suggests both bonding and bridging capital in prisoner populations due for release and the diversity of community capital opportunities that exists in this population. The implications of this work are significant for substance users and offenders pending return to the community, and has implications around resettlement and reintegration support for probation staff in prisons and in the community. The paper emphasises the importance of mapping connectedness as a key component of planning for reintegration back into the community for those working with offenders who are aspiring to achieve desistance and recovery.


Urban Studies ◽  
2020 ◽  
pp. 004209802092537
Author(s):  
Leen Vandecasteele ◽  
Anette Eva Fasang

We bring together research on social networks and neighbourhood disadvantage to examine how they jointly affect unemployed individuals’ probability of re-entering employment. Data from the UK Household Longitudinal Study ‘Understanding Society’ provide information on the proportion of friends who live in the same neighbourhood, and are linked with small-scale administrative information on neighborhood employment deprivation. Results indicate that neighbourhood employment deprivation prolongs unemployment, but only for individuals who report that all of their friends live in the same neighbourhood. Living in an advantaged neighbourhood with all of one’s friends in the neighbourhood increases the chances of exiting unemployment. In contrast, neighbourhood location is not associated with unemployment exit if one’s friends do not live in the same neighbourhood. We conclude that neighbourhood effects on exiting unemployment critically depend on individuals’ social embeddedness in the neighbourhood. Not just residing in a disadvantaged neighbourhood, but actually living there with all one’s friends, prevents individuals from re-entering employment. This opens new avenues for theorising neighbourhood effects as social rather than geographic phenomena, and highlights that the effects of neighbourhood socio-economic characteristics are conditional on the level of interaction residents have within their neighbourhood.


Author(s):  
Miroslava Raspopovic Milic ◽  
Milena Vukmirovic ◽  
Svetlana Cvetanovic

Tourism in rural areas is considered small-scale tourism, which represents a strong potential for growth of areas traditionally characterized as agricultural areas. Rural tourism tends to be heterogeneous with many different and scattered stakeholders, making the efficiency and effectivity hard to achieve. Many ICT technologies have found their way into smart tourism. Even though there are plentiful user generated data and smart tourism applications, they represent a very heterogeneous sources that are challenging to integrate in one scalable system. The aim of this research is to propose a model for information system that will increase efficiency of the rural small-scale tourism by using both internal and external systems, such as social networks, local services, geotagged resources, sentiment analysis, and data- and text-based mining systems. The goal of this information system is to gather a rich database that will allow users to identify their next destination and to identify most valuable assets for each location in the region.


2021 ◽  
pp. 133-163
Author(s):  
Jan Fuhse

This chapter develops a relational sociological account of the interplay of networks of social relationships with wider culture around the notions of role and institution. Roles mediate between the structure of social networks and institutionalized cultural patterns: On the one hand, they can emerge in small-scale network contexts and crystallize as long as the network structure persists. On the other hand, communication draws on institutionalized models to reduce its complexity and uncertainty. Relational institutions thereby imprint social networks by role categories. Such relational institutions include cultural models for actorhood, for social relationships (“relationship frames”), and for patterns of relationships. The chapter combines the general perspective of relational sociology with arguments from social network research, role theory, philosophical anthropology, and neo-institutionalism.


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