Team performance according to ball possession characteristics : a social networks approach

Over the last few years, football entered in a period of accelerated access to large amount of match analysis data. Social networks have been adopted to reveal the structure and organization of the web of interactions, such as the players passing distribution tendencies. In this study we investigated the influence of ball possession characteristics in the competitive success of Spanish La Liga teams. The sample was composed by OPTA passing distribution raw data (n=269,055 passes) obtained from 380 matches involving all the 20 teams of the 2012/2013 season. Then, we generated 760 adjacency matrixes and their corresponding social networks using Node XL software. For each network we calculated three team performance measures to evaluate ball possession tendencies: graph density, average clustering and passing intensity. Three levels of competitive success were determined using two-step cluster analysis based on two input variables: the total points scored by each team and the scored per conceded goals ratio. Our analyses revealed significant differences between competitive performances on all the three team performance measures (p < .001). Bottom-ranked teams had less number of connected players (graph density) and triangulations (average clustering) than intermediate and top-ranked teams. However, all the three clusters diverged in terms of passing intensity, with top-ranked teams having higher number of passes per possession time, than intermediate and bottom-ranked teams. Finally, similarities and dissimilarities in team signatures of play between the 20 teams were displayed using Cohen’s effect size. In sum, findings suggest the competitive performance was influenced by the density and connectivity of the teams, mainly due to the way teams use their possession time to give intensity to their game.

Funzioni di Matrici. Proprieta' e applicazione ai social networks

Teoria delle funzioni di matrici. Spiegazione del concetto di network, proprietà rilevanti rilevate attraverso determinate funzioni di matrici. Applicazione della teoria a due esempi di network reali.

Social networks in Argentinian libraries : Tips to formulate a communicational policy

En base a los resultados obtenidos en investigaciones efectuadas por el grupo de investigación del Instituto de Investigaciones en Humanidades y Ciencias Sociales (UNLP-CONICET) sobre redes sociales en distintos tipos de bibliotecas (de investigación, universitarias y populares) en Argentina, se efectúa un balance sobre su uso en este tipo de instituciones y se proponen lineamientos para la formulación de una política comunicacional que las contemple y forme parte del plan de gestión de estas unidades de información. Los mismos apuntan a considerar cabalmente todos los aspectos vinculados a los alcances, limitaciones, usos, riesgos y demás que implica la adopción y la apropiación de diferentes redes sociales (tales como Facebook, Twitter, entre otras), su convivencia, gestión y sustentabilidad a lo largo del tiempo

Essays on social networks, altruism and information diffusion

This dissertation consists of three standalone articles that contribute to the economics literature concerning technology adoption, information diffusion, and network economics in one way or another, using a couple of primary data sources from Ethiopia. The first empirical paper identifies the main behavioral factors affecting the adoption of brand new (radical) and upgraded (incremental) bioenergy innovations in Ethiopia. The results highlight the importance of targeting different instruments to increase the adoption rate of the two types of innovations. The second and the third empirical papers of this thesis, use primary data collected from 3,693 high school students in Ethiopia, and shed light on how we should select informants to effectively and equitably disseminate new information, mainly concerning environmental issues. There are different well-recognized standard centrality measures that are used to select informants. These standard centrality measures, however, are based on the network topology---shaped only by the number of connections---and fail to incorporate the intrinsic motivations of the informants. This thesis introduces an augmented centrality measure (ACM) by modifying the eigenvector centrality measure through weighting the adjacency matrix with the altruism levels of connected nodes. The results from the two papers suggest that targeting informants based on network position and behavioral attributes ensures more effective and equitable (gender perspective) transmission of information in social networks than selecting informants on network centrality measures alone. Notably, when the information is concerned with environmental issues.

Mutual trust and cooperation in the evolutionary hawks-doves game

Using a new dynamical network model of society in which pairwise interactions are weighted according to mutual satisfaction, we show that cooperation is the norm in the hawks-doves game when individuals are allowed to break ties with undesirable neighbors and to make new acquaintances in their extended neighborhood. Moreover, cooperation is robust with respect to rather strong strategy perturbations. We also discuss the empirical structure of the emerging networks, and the reasons that allow cooperators to thrive in the population. Given the metaphorical importance of this game for social interaction, this is an encouraging positive result as standard theory for large mixing populations prescribes that a certain fraction of defectors must always exist at equilibrium.

Facebook faith - social networking in a faith based community

This paper views the increasing social networking as an efficient emerging ministry to the moveable generation. Through social network such as Facebook, ministry from a pastoral perspective can become more authentic and meaningful. Ministry is relational. Social Networking sites provide a strong platform to being part in other people’s life. Social networking and living online builds community beyond geographical boarders. Young adults and youths digital identity often reflects their faith, this is supported by research which suggests a practice of more openness to share and expose private issues online. Spiritual and religious views are freely shared, creating sacred spaces in the midst of life practising a holistic faith identity in a secular community. Providing a strong platform for information flow, Social Network is attractive in a postmodern society where inviting people to join in events are perceived as non threatening, making church community events transparent and available to people who do not attend church, inviting spiritual friendships and relationships. Social Networking strengthens relationship in a non hierarchical manner and invites the minister into lives where there previously would have been barriers, engaging in prayer and bible study as well as pastoral care through social networking, thus relationships deepens via social networking making people real. It has been observed that, although community building happens on the net, church affiliation loyalty remains to the local community. Therefore presence ministry though social networks emerges as a core form of ministry, where relations to youth who move from local church to university campuses are kept alive. The asynchronous nature of communication within social networking eases the minister in her work. The minister is able to engage with many individuals at the same time. Before the minister could visit one person at a time, now she visits 5-6 individuals at any given time. Therefore social networking not only increases the quality of the work, but also empowers the minister to be more efficient.

Boosting optimum-path forest clustering through harmony Search and its applications for intrusion detection in computer networks

In this paper we propose a nature-inspired approach that can boost the Optimum-Path Forest (OPF) clustering algorithm by optimizing its parameters in a discrete lattice. The experiments in two public datasets have shown that the proposed algorithm can achieve similar parameters' values compared to the exhaustive search. Although, the proposed technique is faster than the traditional one, being interesting for intrusion detection in large scale traffic networks. © 2012 IEEE.

Fuzzy community structure detection by particle competition and cooperation

Identification and classification of overlapping nodes in networks are important topics in data mining. In this paper, a network-based (graph-based) semi-supervised learning method is proposed. It is based on competition and cooperation among walking particles in a network to uncover overlapping nodes by generating continuous-valued outputs (soft labels), corresponding to the levels of membership from the nodes to each of the communities. Moreover, the proposed method can be applied to detect overlapping data items in a data set of general form, such as a vector-based data set, once it is transformed to a network. Usually, label propagation involves risks of error amplification. In order to avoid this problem, the proposed method offers a mechanism to identify outliers among the labeled data items, and consequently prevents error propagation from such outliers. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method. © 2012 Springer-Verlag.

Performance of an abbreviated version of the Lubben Social Network Scale among three European community-dwelling older adult populations

PURPOSE: There is a need for valid and reliable short scales that can be used to assess social networks and social supports and to screen for social isolation in older persons. DESIGN AND METHODS: The present study is a cross-national and cross-cultural evaluation of the performance of an abbreviated version of the Lubben Social Network Scale (LSNS-6), which was used to screen for social isolation among community-dwelling older adult populations in three European countries. Based on the concept of lack of redundancy of social ties we defined clinical cut-points of the LSNS-6 for identifying persons deemed at risk for social isolation. RESULTS: Among all three samples, the LSNS-6 and two subscales (Family and Friends) demonstrated high levels of internal consistency, stable factor structures, and high correlations with criterion variables. The proposed clinical cut-points showed good convergent validity, and classified 20% of the respondents in Hamburg, 11% of those in Solothurn (Switzerland), and 15% of those in London as at risk for social isolation. IMPLICATIONS: We conclude that abbreviated scales such as the LSNS-6 should be considered for inclusion in practice protocols of gerontological practitioners. Screening older persons based on the LSNS-6 provides quantitative information on their family and friendship ties, and identifies persons at increased risk for social isolation who might benefit from in-depth assessment and targeted interventions.

Implications of social capital for the inclusion of people with disabilities and families in community life

This paper seeks to ascertain the usefulness of the theory of social capital as a framework for developing and sustaining the inclusion of people with disabilities and families in community life. We discuss the theoretical elements of social capital and assess its relevance when understanding both the experiences of people with disabilities and their families and the possible implications for policy and programme efforts to promote inclusion. Preliminary findings from two studies of the experiences and social networks of people with disabilities and their families in communities in regional and rural Australia are presented. It is argued that to date, people with disabilities and their families have largely been excluded from the broader social capital debate and that social capital thinking has had minimal influence on efforts to achieve the inclusion of people with disabilities into community life. It is further argued that new paradigms of support are needed that build capacity and social capital through working alongside individuals and families to influence not only outcomes for them, but also for the communities on which they live. The local area coordination model as it has developed in Australia since 1989 provides some instructive signposts for integrating individual, family and community approaches. It is concluded that social capital theory can make a contribution to inclusion theory and practice but we should use it with circumspection.

Measuring community strength and social capital

Five case study communities in both metropolitan and regional urban locations in Australia are used as test sites to develop measures of 'community strength' on four domains: Natural Capital; Produced Economic Capital; Human Capital; and Social and Institutional Capital. The paper focuses on the fourth domain. Sample surveys of households in the five case study communities used a survey instrument with scaled items to measure four aspects of social capital - formal norms, informal norms, formal structures and informal structures - that embrace the concepts of trust, reciprocity, bonds, bridges, links and networks in the interaction of individuals with their community inherent in the notion social capital. Exploratory principal components analysis is used to identify factors that measure those aspects of social and institutional capital, while a confirmatory analysis based on Cronbach's alpha explores the robustness of the measures. Four primary scales and 15 subscales are identified when defining the domain of social and institutional capital. Further analysis reveals that two measures - anomie, and perceived quality of life and wellbeing - relate to certain primary scales of social capital.

Data surveillance for infectious diseases: models, complex networks and machine learning

In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.

Who supports? The providers of social support to dual-parent families caring for young children

Previous research points to the importance of both kin and non-kin ties within social networks as sources of social support. This study examines the kin and non-kin providers of specific types of support to dual-parent low-income Australian families caring for young children. The study highlights the importance of family and friends as support providers. Study Participants tended to rely on family, including parents, siblings and other family members, and friends for emotional and information support. Parents also tended to provide material and practical support. While neighbors and community agencies offered some emotional and information support, overall, these sources were minimal. (C) 2002 Wiley Periodicals, Inc.

The perceived potential of business social networking sites

Business social networking is a facilitator of several business activities, such as market studies, communication with clients, and identification of business partners. This paper traduces the results of a study undertaken with the purpose of getting to know how the potential of networking is perceived in the promotion of business by participants of the LinkedIn network, and presents two main contributions: (1) to disseminate within the business community which is the relevance given to social networking; and (2) which are the social networks best suitable to the promotion of business, to support the definition of strategies and approaches accordingly. The results confirm that LinkedIn is the most suitable network to answer the needs of those that look for professional contacts and for the promotion of business, while innovation is the most recognized factor in the promotion of business through social networking. This study contributes to a better understanding of the potential of different business social networking sites, to support organizations and professionals to align their strategies with the perceived potential of each network.