Russian social networks on the web: cohesion and coherence in Vkontakte

In this thesis connections between messages on the public wall of the Russian social network Vkontakte are analysed and classified. A total of 1818 messages from three different Vkontakte groups were collected and analysed according to a new framework based on Halliday and Hasan’s (1976) research into cohesion and Simmons’s (1981) adaptation of their classification for Russian. The two categories of textuality, cohesion and coherence, describe the linguistic connections between messages. The main aim was to find out how far the traditional categories of cohesion are applicable to an online social network including written text as well as multimedia-files. In addition to linguistic cohesion the pragmatic and topic coherence between Vkontakte messages was also analysed. The analysis of pragmatic coherence classifies the messages with acts according to their pragmatic function in relation to surrounding messages. Topic coherence analyses the content of the messages, describes where a topic begins, changes or is abandoned. Linguistic cohesion, topic coherence and pragmatic coherence enable three different types of connections between messages and these together form a coherent communication on the message wall. The cohesion devices identified by Halliday and Hasan and Simmons were found to occur in these texts, but additional devices were also identified: these are multimodal, graphical and grammatical cohesion.

ADVERTISEMENT ALLOCATION AND TRUST MECHANISMS DESIGN IN SOCIAL NETWORKS

Social network sites (SNS), such as Facebook, Google+ and Twitter, have attracted hundreds of millions of users daily since their appearance. Within SNS, users connect to each other, express their identity, disseminate information and form cooperation by interacting with their connected peers. The increasing popularity and ubiquity of SNS usage and the invaluable user behaviors and connections give birth to many applications and business models. We look into several important problems within the social network ecosystem. The first one is the SNS advertisement allocation problem. The other two are related to trust mechanisms design in social network setting, including local trust inference and global trust evaluation. In SNS advertising, we study the problem of advertisement allocation from the ad platform's angle, and discuss its differences with the advertising model in the search engine setting. By leveraging the connection between social networks and hyperbolic geometry, we propose to solve the problem via approximation using hyperbolic embedding and convex optimization. A hyperbolic embedding method, \hcm, is designed for the SNS ad allocation problem, and several components are introduced to realize the optimization formulation. We show the advantages of our new approach in solving the problem compared to the baseline integer programming (IP) formulation. In studying the problem of trust mechanisms in social networks, we consider the existence of distrust (i.e. negative trust) relationships, and differentiate between the concept of local trust and global trust in social network setting. In the problem of local trust inference, we propose a 2-D trust model. Based on the model, we develop a semiring-based trust inference framework. In global trust evaluation, we consider a general setting with conflicting opinions, and propose a consensus-based approach to solve the complex problem in signed trust networks.

Mathematical Programming Models for Influence Maximization on Social Networks

In this dissertation, we apply mathematical programming techniques (i.e., integer programming and polyhedral combinatorics) to develop exact approaches for influence maximization on social networks. We study four combinatorial optimization problems that deal with maximizing influence at minimum cost over a social network. To our knowl- edge, all previous work to date involving influence maximization problems has focused on heuristics and approximation. We start with the following viral marketing problem that has attracted a significant amount of interest from the computer science literature. Given a social network, find a target set of customers to seed with a product. Then, a cascade will be caused by these initial adopters and other people start to adopt this product due to the influence they re- ceive from earlier adopters. The idea is to find the minimum cost that results in the entire network adopting the product. We first study a problem called the Weighted Target Set Selection (WTSS) Prob- lem. In the WTSS problem, the diffusion can take place over as many time periods as needed and a free product is given out to the individuals in the target set. Restricting the number of time periods that the diffusion takes place over to be one, we obtain a problem called the Positive Influence Dominating Set (PIDS) problem. Next, incorporating partial incentives, we consider a problem called the Least Cost Influence Problem (LCIP). The fourth problem studied is the One Time Period Least Cost Influence Problem (1TPLCIP) which is identical to the LCIP except that we restrict the number of time periods that the diffusion takes place over to be one. We apply a common research paradigm to each of these four problems. First, we work on special graphs: trees and cycles. Based on the insights we obtain from special graphs, we develop efficient methods for general graphs. On trees, first, we propose a polynomial time algorithm. More importantly, we present a tight and compact extended formulation. We also project the extended formulation onto the space of the natural vari- ables that gives the polytope on trees. Next, building upon the result for trees---we derive the polytope on cycles for the WTSS problem; as well as a polynomial time algorithm on cycles. This leads to our contribution on general graphs. For the WTSS problem and the LCIP, using the observation that the influence propagation network must be a directed acyclic graph (DAG), the strong formulation for trees can be embedded into a formulation on general graphs. We use this to design and implement a branch-and-cut approach for the WTSS problem and the LCIP. In our computational study, we are able to obtain high quality solutions for random graph instances with up to 10,000 nodes and 20,000 edges (40,000 arcs) within a reasonable amount of time.

Determinants of engagement in virtual social networks in Singapore

The use of virtual social networks (VSNs) has been prevalent among consumers worldwide. Numerous studies have investigated various aspects of VSNs. However, these studies have mainly focused on students and young adults as they were early adopters of these innovative networks. A search of the literature revealed there has been a paucity of research on adult consumers’ use of VSNs. This research study addressed this gap in the literature by examining the determinants of engagement in VSNs among adult consumers in Singapore. The objectives of this study are to empirically investigate the determinants of engagement in VSNs and to offer theoretical insights into consumers’ preference and usage of VSNs. This study tapped upon several theories developed in the discipline of technology and innovation adoption. These were Roger’s Diffusion of Innovation, Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), Conceptual Framework of Individual Innovation Adoption by Frambach and Schillewaert (2002), Enhanced Model of Innovation Adoption by Talukder (2011), Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Information Systems (IS) Success Model. The proposed research model, named the Media Usage Model (MUM), is a framework rooted in innovation diffusion and IS theories. The MUM distilled the essence of these established models and thus provides an updated, lucid explanation of engagement in VSNs. A cross-sectional, online social survey was conducted to collect quantitative data to examine the validity of the proposed research model. Multivariate data analysis was carried out on a data set comprising 806 usable responses by utilizing SPSS, and for structural equation modeling AMOS and SmartPLS. The results indicate that consumer attitude towards VSNs is significantly and positively influenced by: three individual factors – hedonic motivation, incentives and experience; two system characteristics – system quality and information quality; and one social factor – social bonding. Consumer demographics were found to influence people’s attitudes towards VSNs. In addition, consumer experience and attitude towards VSNs significantly and positively influence their usage of VSNs. The empirical data supported the proposed research model, explaining 80% of variance in attitude towards VSNs and 45% of variance in usage of VSNs. Therefore, the MUM achieves a definite contribution to theoretical knowledge of consumer engagement in VSNs by deepening and broadening our appreciation of the intricacies related to use of VSNs in Singapore. This study’s findings have implications for customer service management, services marketing and consumer behavior. These findings also have strategic implications for maximizing efficient utilization and effective management of VSNs by businesses and operators. The contributions of this research are: firstly, shifting the boundaries of technology or innovation adoption theories from research on employees to consumers as well as the boundaries of Internet usage or adoption research from students to adults, which is also known as empirical generalization; secondly, highlighting the issues associated with lack of significance of social factors in adoption research; and thirdly, augmenting information systems research by integrating important antecedents for success in information systems.

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.

Semantic social network analysis

Mestrado em Engenharia Informática

Distributed Forest Fire Monitoring Using Wireless Sensor Networks

Disaster management is one of the most relevant application fields of wireless sensor networks. In this application, the role of the sensor network usually consists of obtaining a representation or a model of a physical phenomenon spreading through the affected area. In this work we focus on forest firefighting operations, proposing three fully distributed ways for approximating the actual shape of the fire. In the simplest approach, a circular burnt area is assumed around each node that has detected the fire and the union of these circles gives the overall fire’s shape. However, as this approach makes an intensive use of the wireless sensor network resources, we have proposed to incorporate two in-network aggregation techniques, which do not require considering the complete set of fire detections. The first technique models the fire by means of a complex shape composed of multiple convex hulls representing different burning areas, while the second technique uses a set of arbitrary polygons. Performance evaluation of realistic fire models on computer simulations reveals that the method based on arbitrary polygons obtains an improvement of 20% in terms of accuracy of the fire shape approximation, reducing the overhead in-network resources to 10% in the best case.

Learning networks and moodle use in online courses: a social network analysis study

Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação

Percolation of spatially constrained Erdos-R enyi networks with degree correlations

Motivated by experiments on activity in neuronal cultures [J. Soriano, M. Rodr ́ıguez Mart́ınez, T. Tlusty, and E. Moses, Proc. Natl. Acad. Sci. 105, 13758 (2008)], we investigate the percolation transition and critical exponents of spatially embedded Erd̋os-Ŕenyi networks with degree correlations. In our model networks, nodes are randomly distributed in a two-dimensional spatial domain, and the connection probability depends on Euclidian link length by a power law as well as on the degrees of linked nodes. Generally, spatial constraints lead to higher percolation thresholds in the sense that more links are needed to achieve global connectivity. However, degree correlations favor or do not favor percolation depending on the connectivity rules. We employ two construction methods to introduce degree correlations. In the first one, nodes stay homogeneously distributed and are connected via a distance- and degree-dependent probability. We observe that assortativity in the resulting network leads to a decrease of the percolation threshold. In the second construction methods, nodes are first spatially segregated depending on their degree and afterwards connected with a distance-dependent probability. In this segregated model, we find a threshold increase that accompanies the rising assortativity. Additionally, when the network is constructed in a disassortative way, we observe that this property has little effect on the percolation transition.

Networks 3: Social Structures

A brief look at the post-industrial, network society, freed from manual labour and liberated from place.

BlueFriends: measuring, analyzing and preventing social exclusion between elementary school students

Social exclusion is a relatively recent term, whose creation is attributed to René Lenoir(Lenoir, 1974). Its concept covers a remarkably wide range of social and economic problems, and can be triggered for various reasons: mentally and physically handicapped, abused children, delinquents, multi-problem households, asocial people, and other social “misfits” (Silver, 1995, pp. 63; Foucault, 1992). With an increasingly multi-cultural population, cultural and social inequalities rapidly ascend, bringing with them the need for educational restructuring. We are living in an evermore diverse world, and children need to be educated to be receptive to the different types of people around them, especially considering social and cultural aspects. It is with these goals that inclusive education has seen an increased trend in today’s academic environment, reminding us that even though children may be taught under the same roof, discriminatory practices might still happen. There are, however, a number of developed tools to assess the various dimensions of social networks. These are mostly based on questionnaires and interviews, which tend to be fastidious and don’t allow for longitudinal, large scale measurement. This thesis introduces BlueFriends, a Bluetooth-based measurement tool for social inclusion/exclusion on elementary school classes. The main goals behind the development of this tool were a) understanding how exclusion manifests in students’ behaviors, and b) motivating pro-social behaviors on children through the use of a persuasive technology. BlueFriends is a distributed application, comprised by an application running on several smartphones, a web-hosted database and a computer providing a visual representation of the data collected on a TV screen, attempting to influence children behaviors. The application makes use of the Bluetooth device present on each phone to continuously sample the RSSI (Received Signal Strength Indication) from other phones, storing the data locally on each phone. All of the stored data is collected, processed and then inserted into the database at the end of each day. At the beginning of each recess, children are reminded of how their behaviors affect others with the help of a visual display, which consists of interactions between dogs. This display illustrates every child’s best friends, as well as which colleagues they don’t interact with as much. Several tips encouraging social interaction and inclusiveness are displayed, inspiring children to change their behaviors towards the colleagues they spend less time with. This thesis documents the process of designing, deploying and analyzing the results of two field studies. On the first study, we assess how the current developed tools are inferior to our measuring tool by deploying a measurement only study, aimed at perceiving how much information can be obtained by the BlueFriends application and attempting to understand how exclusion manifests itself in the school environment. On the second study, we pile on the previous to try and motivate pro-social behaviors on students, with the use of visual cues and recommendations. Ultimately, we confirm that our measurement tool’s results were satisfying towards measuring and changing children’s behaviors, and conclude with our thoughts on possible future work, suggesting a number of possible extensions and improvements.