Temporal Features as Measures of Tie Strength in Mobile Phone Networks

The use of auto-recorded communication data, such as mobile phone call logs, has reshaped our capacity to model and understand of social systems. In such studies, the strength of a tie between two people has been of great value from both theoretical and sociological perspectives, yet it is not easy to quantify. Tie strengths are commonly measured in terms of communication intensity (number or duration of calls, etc) as a form of convenience rather than a justified choice, yet these intensity-based measures do not uncover the myriad of ways in which such intensity takes place, hindering information about the strength of ties. Here, we conceive tie strength as a latent variable we want to predict based on features of the time sequences of interactions. We assume that tie strength is expressed as the structural overlap in social networks, in a manner inspired by Granovetter's hypothesis, where strong ties are embedded in community structures, while weak ties serve as inter-community bridges. With this assumption, we use temporal and static features to predict overlap in lieu of the latent tie strength. We analyze a mobile phone dataset of ~6.5 million people for a period of 4 months, and measure overlap based on an extended network of ~77 million users, to ensure minimal sampling errors. We observe a strong relationship between local topology and tie-level behaviour, with some temporal features outperforming communication intensity in overlap prediction. Indeed, the number of bursty cascades, differences in daily behaviour and temporal stability play large roles in our models. We find that communication intensity is one of many characterizations of tie strength for which the Granovetter effect is observable

Socioscope: Human Relationship and Behavior Analysis in Mobile Social Networks

The widely used mobile phone, as well as its related technologies had opened opportunities for a complete change on how people interact and build relationship across geographic and time considerations. The convenience of instant communication by mobile phones that broke the barrier of space and time is evidently the key motivational point on why such technologies so important in people's life and daily activities. Mobile phones have become the most popular communication tools. Mobile phone technology is apparently changing our relationship to each other in our work and lives. The impact of new technologies on people's lives in social spaces gives us the chance to rethink the possibilities of technologies in social interaction. Accordingly, mobile phones are basically changing social relations in ways that are intricate to measure with any precision. In this dissertation I propose a socioscope model for social network, relationship and human behavior analysis based on mobile phone call detail records. Because of the diversities and complexities of human social behavior, one technique cannot detect different features of human social behaviors. Therefore I use multiple probability and statistical methods for quantifying social groups, relationships and communication patterns, for predicting social tie strengths and for detecting human behavior changes and unusual consumption events. I propose a new reciprocity index to measure the level of reciprocity between users and their communication partners. The experimental results show that this approach is effective. Among other applications, this work is useful for homeland security, detection of unwanted calls (e.g., spam), telecommunication presence, and marketing. In my future work I plan to analyze and study the social network dynamics and evolution

Insight into social physics: uncovering the structure and dynamics of social relationships

This thesis investigates the emerging interdisciplinary field of social physics, which applies concepts and methods from physics, mathematics and anthropology to understand human behaviour in social systems. Our research seeks to elucidate how humans organise their social relationships and how they evolve over time by examining the universal principles underpinning these phenomena. The basis of our investigation is the concept of “social atom”, which serves as a foundation for studying ego-networks at the micro-level and exploring the collective behaviour of social systems at the macro-level. We embark on two complementary research approaches to address this complex problem. Our first approach involves conducting field research by surveying high school students about their friendships and enmities over two academic years. This empirical data enables us to analyse the organisation and evolution of social relationships, providing valuable insights that can be shared with school principals to foster a more positive social atmosphere and prevent important issues such as bullying. Our second approach aligns with the conventional scientific method. It involves the formulation of hypotheses, the development of network models and their testing. To do that, we employ exponential random graph models and density functional theory, a technique originating from statistical mechanics for analysing lattice gases. This approach demonstrates that social networks can exhibit phenomena comparable to those observed in fluids or gases, such as phase transitions. These findings contribute to a more profound understanding of the behaviour exhibited by social systems. Moreover, we expand the applicability of these models to include other species, such as primates, demonstrating their relevance beyond human social relationships. We establish a formalism that can be employed to address social physics problems more effectively by synthesising the insights derived from both research approaches. This integrative method advances our understanding of the discipline and paves the way for more accurate and effective solutions. Through the combination of field research, network modelling and the extension of these models to other species, this thesis makes a substantial contribution to the field of social physics. Our research provides a solid foundation for future studies and applications aimed at improving the understanding and management of complex social systems by uncovering the fundamental mechanisms governing human social behaviour.Programa de Doctorado en Ingeniería Matemática por la Universidad Carlos III de MadridPresidente: Luis Mario Floria Peralta.- Secretario: Alberto Antonioni.- Vocal: María Pereda Garcí

Events in social networks : a stochastic actor-oriented framework for dynamic event processes in social networks

Interactions between people are ubiquitous. When people make phone calls, transfer money, connect on social network sites, or visit each other, these actions can be collected as dyadic, directed, relational events. Each of those events can be understood as driven by multiple individual decisions that at least partially involve rational considerations. This book aims at developing models that allow to understand individual event decisions in the context of large social networks

PROFILING - CONCEPTS AND APPLICATIONS

Profiling is an approach to put a label or a set of labels on a subject, considering the characteristics of this subject. The New Oxford American Dictionary defines profiling as: “recording and analysis of a person’s psychological and behavioral characteristics, so as to assess or predict his/her capabilities in a certain sphere or to assist in identifying a particular subgroup of people”. This research extends this definition towards things demonstrating that many methods used for profiling of people may be applied for a different type of subjects, namely things. The goal of this research concerns proposing methods for discovery of profiles of users and things with application of Data Science methods. The profiles are utilized in vertical and 2 horizontal scenarios and concern such domains as smart grid and telecommunication (vertical scenarios), and support provided both for the needs of authorization and personalization (horizontal usage).:The thesis consists of eight chapters including an introduction and a summary. First chapter describes motivation for work that was carried out for the last 8 years together with discussion on its importance both for research and business practice. The motivation for this work is much broader and emerges also from business importance of profiling and personalization. The introduction summarizes major research directions, provides research questions, goals and supplementary objectives addressed in the thesis. Research methodology is also described, showing impact of methodological aspects on the work undertaken. Chapter 2 provides introduction to the notion of profiling. The definition of profiling is introduced. Here, also a relation of a user profile to an identity is discussed. The papers included in this chapter show not only how broadly a profile may be understood, but also how a profile may be constructed considering different data sources. Profiling methods are introduced in Chapter 3. This chapter refers to the notion of a profile developed using the BFI-44 personality test and outcomes of a survey related to color preferences of people with a specific personality. Moreover, insights into profiling of relations between people are provided, with a focus on quality of a relation emerging from contacts between two entities. Chapters from 4 to 7 present different scenarios that benefit from application of profiling methods. Chapter 4 starts with introducing the notion of a public utility company that in the thesis is discussed using examples from smart grid and telecommunication. Then, in chapter 4 follows a description of research results regarding profiling for the smart grid, focusing on a profile of a prosumer and forecasting demand and production of the electric energy in the smart grid what can be influenced e.g. by weather or profiles of appliances. Chapter 5 presents application of profiling techniques in the field of telecommunication. Besides presenting profiling methods based on telecommunication data, in particular on Call Detail Records, also scenarios and issues related to privacy and trust are addressed. Chapter 6 and Chapter 7 target at horizontal applications of profiling that may be of benefit for multiple domains. Chapter 6 concerns profiling for authentication using un-typical data sources such as Call Detail Records or data from a mobile phone describing the user behavior. Besides proposing methods, also limitations are discussed. In addition, as a side research effect a methodology for evaluation of authentication methods is proposed. Chapter 7 concerns personalization and consists of two diverse parts. Firstly, behavioral profiles to change interface and behavior of the system are proposed and applied. The performance of solutions personalizing content either locally or on the server is studied. Then, profiles of customers of shopping centers are created based on paths identified using Call Detail Records. The analysis demonstrates that the data that is collected for one purpose, may significantly influence other business scenarios. Chapter 8 summarizes the research results achieved by the author of this document. It presents contribution over state of the art as well as some insights into the future work planned

Peer influence in the diffusion of iPhone 3G over a large social network

In this paper, we study the effect of peer influence in the diffusion of the iPhone 3G across a number of communities sampled from a large dataset provided by a major European Mobile carrier in one country. We identify tight communities of users in which peer influence may play a role and use instrumental variables to control for potential correlation between unobserved subscriber heterogeneity and friends' adoption. We provide evidence that the propensity of a subscriber to adopt increases with the percentage of friends who have already adopted. During a period of 11 months, we estimate that 14 percent of iPhone 3Gs sold by this carrier were due to peer influence. This result is obtained after controlling for social clustering, gender, previous adoption of mobile Internet data plans, ownership of technologically advanced handsets, and heterogeneity in the regions where subscribers move during the day and spend most of their evenings. This result remains qualitatively unchanged when we control for changes over time in the structure of the social network. We provide results from several policy experiments showing that, with this level of effect of peer influence, the carrier would have hardly benefitted from using traditional marketing strategies to seed the iPhone 3G to benefit from viral marketing.info:eu-repo/semantics/publishedVersio

Ego-centred models of social networks: the social atom

Mención Internacional en el título de doctorThis thesis set out to contribute to the realm of social physics, with a particular focus on human social networks. Our approach, however, is somewhat di erent from what is typical in disciplines such as complex systems or statistical physics. Rather than simplifying the features of the constituents of our system (people), and stressing their rules of interaction, we focus on better understanding those very same constituents, modelling them as social atoms. Our rationale is that a better understanding of such an atom may shed light on how (and why) it interacts with other atoms to form social collectives. Given its robustness and the evolutionary roots of its premises, we use the Social Brain Hypothesis as our departure point. This theory states that the evolutionary drive behind the development of large brains in humans was the need to process social information and that the limited capacity of our brains imposes a limit to the number of relationships we can manage— the so-called “Dunbar’s number”, roughly 150. Moreover, evidence keeps revealing that these relationships are further organised in a series of hierarchically inclusive layers with decreasing emotional intensity, whose sizes exhibit a more or less constant scaling. Notwithstanding the empirical evidence, neither the presence of scaling in the organisation of personal networks nor its connection with limited cognitive skills had been explained so far. In Chapter 2 we present a mathematical model that solves this puzzle. The assumptions of the model are quite simple, and well founded on empirical evidence. Firstly, the number of relationships we maintain tends to be stable on average. Secondly, these relationships are costly, and our resources are limited. With these two premises, our results show that the hierarchical organisation emerges naturally from the principle of maximum entropy. Not only that, but we also predict a hitherto unnoticed regime of organisation whose existence we prove using several datasets from communities of immigrants. The former model considers that relationships can only belong to a discrete set of categories (layers). In Chapter 3 we extend it so that relationships are classified in a continuum. This modification allows us to test the model with data from very di erent sources such as online communications, face-to-face contacts, and phone calls. Our results show that the two regimes of organisation found in the previous model persist in this variant, and reveal the underlying existence of a (universal) scaling parameter which does not depend on any particular number of layers. To incorporate these ideas into socio-centric models, we build on the so-called Structural Balance Theory. This theory, underpinned by psychological motivations, posits that the structure of social networks of positive and negative relationships are highly interdependent. However, the theory has received little empirical validation, and negative social relationships are poorly understood—both from an ego-centric and a socio-centric perspective. For that reason, we turn to developing an experimental software in order to gather data within a school. In Chapters 4 and 5 we present results from these experiments. In Chapter 4 we analyse the socio-centric networks using machine learning techniques and find that the structure of positive and negative networks is indeed very much connected. Besides, we study the two types of networks separately, showing that they exhibit quite distinct features and that gender e ects in negative social networks are weak and asymmetrical for boys and girls. In Chapter 5, on the other hand, we focus on the structure of negative personal networks. Remarkably, using data from two di erent experimental settings, we show that the structure of personal networks of negative relationships mirrors that of the positive ones and exhibits a similar scaling—albeit their size is significantly smaller. Chapter 6 summarises our results and presents future (and current) lines of investigation. Among them, we outline a model of a social fluid that uses the insights gained with this thesis to build a model of social collectives as ensembles of personal networks. This model is compatible, at the micro-level, with the observations of the social brain hypothesis, and, at the macro-level, with the premises of the structural balance theory.This thesis would not have been possible without the support of Fundación BBVA through its 2016 call project ”Los números de Dunbar y la estructura de las sociedades digitales: modelización y simulación (DUNDIG)”, and we are very thankful for it. Support for early stages of this work through projects IBSEN (European Commission, H2020 FET Open RIA 662725) and VARIANCE (Ministerio de Economía y Competitividad/FEDER, project no. FIS2015-64349-P) is also acknowledgedPrograma Oficial de Doctorado en Ingeniería Matemática por la Universidad Carlos III de MadridPresidente: Javier Martín Buldú.- Secretario: José Luis Molina González.- Vocal: Roberta Sinatr