Analyzing the Facebook Friendship Graph

Online Social Networks (OSN) during last years acquired a\ud huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, our purpose is to analyze Facebook, considering a signi�cant sample of data re\ud ecting relationships among subscribed users. Our goal is to extract, from this platform, relevant information about the distribution of these relations and exploit tools and algorithms provided by the Social Network Analysis (SNA) to discover and, possibly, understand underlying similarities\ud between the developing of OSN and real-life social networks

Exploratory Analysis of Pairwise Interactions in Online Social Networks

In the last few decades sociologists were trying to explain human behaviour by analysing social networks, which requires access to data about interpersonal relationships. This represented a big obstacle in this research field until the emergence of online social networks (OSNs), which vastly facilitated the process of collecting such data. Nowadays, by crawling public profiles on OSNs, it is possible to build a social graph where "friends" on OSN become represented as connected nodes. OSN connection does not necessarily indicate a close real-life relationship, but using OSN interaction records may reveal real-life relationship intensities, a topic which inspired a number of recent researches. Still, published research currently lacks an extensive exploratory analysis of OSN interaction records, i.e. a comprehensive overview of users' interaction via different ways of OSN interaction. In this paper we provide such an overview by leveraging results of conducted extensive social experiment which managed to collect records for over 3,200 Facebook users interacting with over 1,400,000 of their friends. Our exploratory analysis focuses on extracting population distributions and correlation parameters for 13 interaction parameters, providing valuable insight in online social network interaction for future researches aimed at this field of study.Comment: Journal Article published 2 Oct 2017 in Automatika volume 58 issue 4 on pages 422 to 42

Crawling Facebook for Social Network Analysis Purposes

We describe our work in the collection and analysis of massive data describing the connections between participants to online social networks. Alternative approaches to social network data collection are defined and evaluated in practice, against the popular Facebook Web site. Thanks to our ad-hoc, privacy-compliant crawlers, two large samples, comprising millions of connections, have been collected; the data is anonymous and organized as an undirected graph. We describe a set of tools that we developed to analyze specific properties of such social-network graphs, i.e., among others, degree distribution, centrality measures, scaling laws and distribution of friendship.\u

Extraction and Analysis of Facebook Friendship Relations

Online Social Networks (OSNs) are a unique Web and social phenomenon, affecting tastes and behaviors of their users and helping them to maintain/create friendships. It is interesting to analyze the growth and evolution of Online Social Networks both from the point of view of marketing and other of new services and from a scientific viewpoint, since their structure and evolution may share similarities with real-life social networks. In social sciences, several techniques for analyzing (online) social networks have been developed, to evaluate quantitative properties (e.g., defining metrics and measures of structural characteristics of the networks) or qualitative aspects (e.g., studying the attachment model for the network evolution, the binary trust relationships, and the link prediction problem).\ud However, OSN analysis poses novel challenges both to Computer and Social scientists. We present our long-term research effort in analyzing Facebook, the largest and arguably most successful OSN today: it gathers more than 500 million users. Access to data about Facebook users and their friendship relations, is restricted; thus, we acquired the necessary information directly from the front-end of the Web site, in order to reconstruct a sub-graph representing anonymous interconnections among a significant subset of users. We describe our ad-hoc, privacy-compliant crawler for Facebook data extraction. To minimize bias, we adopt two different graph mining techniques: breadth-first search (BFS) and rejection sampling. To analyze the structural properties of samples consisting of millions of nodes, we developed a specific tool for analyzing quantitative and qualitative properties of social networks, adopting and improving existing Social Network Analysis (SNA) techniques and algorithms

Social Network Analysis to Examine the Effectiveness of e-PBL with Design Thinking to Foster Collaboration: Comparisons between High and Low Self-regulated Learners

In TVET teaching and learning, learners’ collaboration is important to ensure learning effectiveness. However, employing either design thinking or online problem-based learning would not lead to fruitarian. Hence, to devise teaching and learning that employs design thinking (DT) and online problem-based learning (ePBL) pedagogies used in tandem with social media learning environment in Facebook are hypothesized to improve TVET learner’s collaboration. By adopting the Social Constructivism learning theory that social interaction fosters collaborative learning and build learners’ knowledge and understanding, this study is commenced. Social interaction that fosters learners’ collaboration is moderated by type of learners’ self-regulation (SR) towards learning. Previous research hypothesized that ePBL alone only worked effectively for high self-regulated learners. The learning outcome inequity present due to the pedagogy limitation. This research devises ePBL with DT as a combination of pedagogies that benefits the low SR learners as well. To monitor collaborative learning occurrences, network ties via social media footprints of individual TVET learners is tracked from the learners’ Facebook group. The effectiveness of treatments is monitored using social network analysis i.e. graph theory and centrality concept employing NodeXL software. Samples of 142 TVET pre-service teachers that currently enroll in Design and Technology course at Teachers’ Training Institutes in Malaysia participated in this study. The samples are intact group and classified into high-SR learners and low-SR learners. Social network analysis using Vertices index, Geodesic distance and graph visualization findings show that ePBL with DT works in fostering learning collaboration for both high-SR and low-SR learners. This implies that national e-learning policy and ePBL embeddedness into technical subject is promising, regardless of the type of learners provided that DT is incorporated into the pedagogy

SPoT: Representing the Social, Spatial, and Temporal Dimensions of Human Mobility with a Unifying Framework

Modeling human mobility is crucial in the analysis and simulation of opportunistic networks, where contacts are exploited as opportunities for peer-topeer message forwarding. The current approach with human mobility modeling has been based on continuously modifying models, trying to embed in them the mobility properties (e.g., visiting patterns to locations or specific distributions of inter-contact times) as they came up from trace analysis. As a consequence, with these models it is difficult, if not impossible, to modify the features of mobility or to control the exact shape of mobility metrics (e.g., modifying the distribution of inter-contact times). For these reasons, in this paper we propose a mobility framework rather than a mobility model, with the explicit goal of providing a exible and controllable tool for modeling mathematically and generating simulatively different possible features of human mobility. Our framework, named SPoT, is able to incorporate the three dimensions - spatial, social, and temporal - of human mobility. The way SPoT does it is by mapping the different social communities of the network into different locations, whose members visit with a configurable temporal pattern. In order to characterize the temporal patterns of user visits to locations and the relative positioning of locations based on their shared users, we analyze the traces of real user movements extracted from three location-based online social networks (Gowalla, Foursquare, and Altergeo). We observe that a Bernoulli process effectively approximates user visits to locations in the majority of cases and that locations that share many common users visiting them frequently tend to be located close to each other. In addition, we use these traces to test the exibility of the framework, and we show that SPoT is able to accurately reproduce the mobility behavior observed in traces. Finally, relying on the Bernoulli assumption for arrival processes, we provide a throughout mathematical analysis of the controllability of the framework, deriving the conditions under which heavy-tailed and exponentially-tailed aggregate inter-contact times (often observed in real traces) emerge

Dinamiche di influenza personale nei Social Network: il caso Twitter

Nei social network online gli utenti svolgono il duplice ruolo di produttori di contenuti e di nodi interni a una rete di contatti personale. Attraverso lo studio del network in cui gli utenti sono inseriti e tramite l’applicazione delle tecniche di social network analysis, è possibile individuare delle dinamiche di influenza personale. Il social network online scelto per l’analisi è Twitter. In primo luogo vengono esposte le ricerche svolte da Lazarsfeld negli anni ’40 nell’ambito dell’influenza personale, quindi, passando in rassegna diversi studi e le loro conclusioni, viene stabilito come le stesse condizioni e gli stessi meccanismi siano in parte validi per analizzare le dinamiche di influenza sul social network

The factors influencing the translation of facebook friendship into real-world friendship.

M. Com. University of KwaZulu-Natal, Durban 2014.Worldwide online social networking sites are the most popular way to make friends. Specifically, Facebook has attracted students from around the world who can connect with other students. It allows students to befriend anyone regardless of race, nationality, ethnicity, language, or gender. As far as the researcher is aware, the factors influencing the translation of Facebook friendship into real-world friendships are uncertain. The present study was therefore conducted to determine to what extent (a) language, (b) race, and (c) gender impact on the translation of Facebook friendship to real-world friendship among university students. This was accomplished through a quantitative method of data collection and analysis. The results indicate that the majority of university students are less likely to convert Facebook friends who speak a different language into real-world friends. In addition, they are unlikely to convert Facebook friends from a different ethnic group into real-world friends. Furthermore, only Black students are likely to convert Facebook friends who speak the same or a different language, as well as come from different ethnic groups, into real-world friends. Whites, Indians and Coloureds are unlikely to do so. Additionally, males are likely to convert female Facebook friends into real-world friends and females are also likely to convert female Facebook friends into real-world friends. Finally, the results show that the vast majority of university students are likely to convert Facebook friends into real-world friends provided they have met in person or if the Facebook friends are considered to be trustworthy

La protección de la intimidad y vida privada en Internet: los flujos de información y la integridad contextual en las redes sociales, (2004-2014)

La presente tesis explora las actuales preocupaciones relativas a las intromisiones en la intimidad y vida privada de las personas producidas en los entornos digitales; concretamente, en las redes sociales. Con el objetivo de entender y explicar los principales riesgos en el uso de estos servicios de Internet, se pretende identificar y evaluar los flujos de información y la transferencia de datos personales que tienen lugar en dichos entornos. Asimismo, tras reseñar los problemas a los que habitualmente se enfrentan los usuarios para preservar, activamente, su esfera privada, se aporta una propuesta destinada a solventar dicha situación de vulnerabilidad, luchando contra la desinformación imperante en dichos contextos. Subrayamos, así, el papel esencial que ostenta el conocimiento, no sólo para prevenir las citadas injerencias, sino para posibilitar que los individuos ejerzan su autodeterminación informativa. Diseño/Metodología/Aproximación: En nuestro estudio haremos uso de las técnicas de análisis de contenido y comparativo aplicadas a una muestra de los más relevantes artículos e informes científicos relativos a las interacciones entre tecnologías digitales de la Web 2.0 e intimidad y vida privada (Existe una cantidad creciente y substancial de literatura que aborda la confrontación entre ambas variables). Ulteriormente, mediante el marco teórico de la “integridad contextual” aportado por Helen Nissenbaum, evaluaremos cómo la naturaleza de la Web 2.0 cambia la ecuación de lo público y lo que se considera privado. A través de las lentes de esta aproximación, analizaremos los flujos de información que se ocultan bajo la estructura de las herramientas de la Web 2.0, centrándonos, primordialmente, en la red social Facebook. Hallazgos/Resultados: Las principales contribuciones de nuestro estudio se resumen en dos. En primer lugar, se consigue ilustrar el papel esencial que el ostenta conocimiento en la propia protección que los usuarios ejercen sobre sus informaciones privadas; ayudándoles a tomar decisiones críticas y conscientes en lo que respecta a la preservación de su ámbito privado. Como segundo aporte, destacamos la presentación de una serie de recomendaciones, así como de un sistema para proporcionar a los individuos ese flujo de información necesario para satisfacer sus deseos de autodeterminación informativa..