The research adopts the technological affordance approach and the theory of planned behavior (TPB) to examine the role of enterprise social media (ESM) in employee communication and its effects on employees in the context of mainland China. The research postulated that organizations can actualize affordances of ESM to influence employees' cognitive perceptions of ESM (i.e., attitude, subjective norms, and perceived behavioral control) that further affect their ESM use intention and relationships with organizations (i.e., employee-organization relationships; EORs). Using a mixed-methods approach to examine Enterprise WeChat (EWeChat), the research interviewed 36 participants to explore organizational actions of EWeChat affordance actualization and employee perceptions about EWeChat use in mainland China. An online survey with 427 mainland Chinese employees adopting EWeChat was conducted to investigate the role of ESM affordance actualization in forming the employees' intention to continuously use EWeChat, as well as in cultivating their EORs through their attitude, subjective norms, perceived behavioral control, and habits of EWeChat use. Key results of the research include the following. Thirteen EWeChat affordances and means of actualization (i.e., association, control, diversity, feedback, outeraction, perpetual contact, persistence, personalization, portability, privacy, social presence, synchronicity, and visibility) for specific organizational goals were identified. The influence of EWeChat affordance actualization on employees' intention to continuously use EWeChat was mediated by their perceived benefits and risks of EWeChat use. The utilitarian benefit, hedonic benefit, avoidance of work-life conflicts, social concerns, privacy concerns, and perceived behavioral control were positive indicators of the continuous EWeChat-use intention, while performance risk was a negative indicator. The effects of affordance actualization on EORs were partially mediated by employees' perceived utilitarian benefit and perceived professional image related to EWeChat use. The research extends the TPB to predict ESM use in Chinese workplaces. It explicates ESM affordance actualization as the interaction between ESM and organization (actor 1), and also between ESM and employees (actor 2). It also evidences that ESM can be used as a relationship cultivation tool. The research sheds light on how organizations in mainland China can effectively configure their ESM to maximize the efficacy and relational outcomes of its mobile application in employee communication

African immigrants in the United States (U.S.) experience immense challenges in the form of poverty, unemployment, and underemployment. One strategy used by community development organizations to address these challenges is the development of farm entry programs that assist immigrants in beginning and sustaining farm operations in the United States. Organizations such as Cooperative Extension, resettlement agencies, and African mutual aid associations have developed beginning farmer programs that provide a supportive foundation for immigrant farmers to gain access to farmland, technical training, and markets.  Returning to farming provides African immigrants with a series of benefits including supplemental income, food security, and social integration. Drawing upon social capital theory, this study offers a novel approach to measure the community and economic development outcomes of immigrant farming programs. In this mixed-method program evaluation, immigrant farming programs are analyzed as social networks that connect immigrants to technical training, farming resources, and community members who can provide access to markets. Data were collected through a survey of 112 agricultural educators working with immigrant farming programs across the United States. Data were also collected through case studies of a Midwestern program and a Southern program. The case studies include two focus groups and 20 interviews with individuals associated with the programs as participants, agricultural educators, and community partners. Regression tests were conducted to determine the social capital factors associated with well-being outcomes occurring through the programs. The models show that interaction outside of the program, and access to information are positively associated with well-being outcomes. Analysis of variance tests show differences between programs with African immigrant participants and programs with participants from other world regions. Programs with African immigrants tend to have more requirements to use farming resources compared to programs with immigrants from other world regions. Qualitative analysis found that female African immigrant participants have a lower levels of agency compared to male African immigrant participants. The study concludes with a discussion of recommendations for implementing and evaluating immigrant farming programs, as well as applying social capital theory to the field of agricultural education. / Ph. D.

En la presente investigación se analizaron las modalidades de contacto presencial y virtual en el desarrollo de vínculo de pareja en la sociedad limeña, con esta finalidad se empleó el modelo teórico de Diaz-Loving para describir la etapa en donde cada participante se encontraba. Se utilizó el método cualitativo, con un diseño fenomenológico; los participantes pertenecían al grupo etario de 19 a 26 años y el instrumento de recolección de información fue la entrevista semiestructurada. Los resultados fueron agrupados en tres categorías: el desarrollo inicial del vínculo, la conquista y el compromiso en la pareja, y la reestructuración del vínculo de pareja. Finalmente, el análisis concluyó que la modalidad de contacto virtual va a intentar aproximarse cada vez más a la modalidad presencial para lograr, dentro de lo posible, que no exista ninguna diferencia en el desarrollo del vínculo entre ambas modalidades. / In the present investigation, the modalities of face-to-face and virtual contact in the development of a relationship in Lima society were analyzed, with this purpose the theoretical Diaz-Loving model was used to describe the stage where each participant was. The qualitative method was used, with a phenomenological design; the participants belonged to the age group from 19 to 26 years old and the information gathering instrument was the semi-structured interview. The results were grouped into three categories: the initial development of the bond, the conquest and commitment in the couple, and the restructuring of the couple bond. Finally, the analysis concluded that the virtual contact modality will try to get closer and closer to the face-to-face modality to achieve, as far as possible, that there is no difference in the development of the bond between both modalities. / Tesis

Despite the growing global momentum and commitment to addressing child malnutrition over the past few decades, undernutrition in children remains a global health crisis, particularly in low- and middle-income countries (LMICs), and leads to deleterious physical and cognitive effects on children. The maternal social network has been linked to child development and health outcomes, partially through its effect on maternal depression, which in turn affects maternal behavior and child health. However, there is limited research in LMICs broadly and in Uganda specifically on the infant/young child caregiving social network, the social network through which mothers receive infant/young child caregiving assistance. This mixed-methods dissertation study piloted and refined a measure to capture this infant/young child caregiving social network in northern Uganda, and then examined sample descriptive data and the associations between networks’ characteristics and maternal depression using a social network analysis (SNA) approach. We also qualitatively examined challenges, barriers, and facilitators to infant and young child caregiving social support. Results found the social network measure to be feasible, acceptable, and comprehensible, and refinements were added to further increase clarity and suitability to the cultural context. Quantitative analyses found higher maternal depression severity to be significantly correlated with lower support on several network characteristics including the average number of caregiving tasks people assisted with, the number of people helping with advanced tasks, and the network density. Further exploration showed that higher network density was also correlated with higher number of tasks alters assisted with. Qualitative results found that mothers often experienced multiple ongoing challenges and barriers in their relationships, such as chronic spousal abuse and financial restriction, and highlighted a lack of systemic support and interventions to address these challenges. We also found several facilitators that helped mothers obtain much needed caregiving support, such as through their older children or Food for the Hungry, a non-profit organization. Though larger future studies are needed to corroborate findings, results of the study may inform interventions for maternal depression and child nutrition/health, identifying possible targets such as network density and highlighting the importance of addressing specific chronic barriers to caregiving social support. Lastly, we also developed a measure that may be used in future studies to examine caregiving networks as a mechanism of change in existing interventions.

The cross-disciplinary Nordic Tweet Stream (NTS) is a project aiming at creating a multilingual text corpus consisting of tweets published in the five Nordic countries. The NTS linguists are explicitly interested in tweets having a text formulated by a human where each tweet is a personal statement, not in Tweets generated by bots and other programs or apps since they might skew the results. NTS consists of multiple parts and the part we are responsible for is a language-independent approach, using supervised machine learning, to classify every single tweet as auto-generated (AGT) or human-generated (HGT). The objective of this study is to increase data accuracy in sociolinguistic studies that utilize Twitter by reducing skewed sampling and inaccuracies in linguistic data. We define an AGT as a tweet where all or parts of the natural language content are generated automatically by a bot or other type of program. In other words, while AGT/HGT refers to an individual message, the term bot refers to nonpersonal and automated accounts that post content to online social networks. Our approach classifies a tweet using only metadata that comes with every tweet, and we utilize those metadata parameters that are both language and country independent. The empirical part shows that our results show poor success rates when it comes to unseen data. Using a bilingual training set of two languages tweets, we correctly classified only about 60-70% of all tweets in a test set using a third new language, which is still better than nothing, but probably not good enough to be used (as is) in a real-world scenario to identify AGTs in a given set of multilingual tweets.

La prolifération des réseaux sociaux et des données à caractère personnel apporte de nombreuses possibilités de développement de nouvelles applications. Au même temps, la disponibilité de grandes quantités de données à caractère personnel soulève des problèmes de confidentialité et de sécurité. Dans cette thèse, nous développons des méthodes pour identifier les différents comptes d'un utilisateur dans des réseaux sociaux. Nous étudions d'abord comment nous pouvons exploiter les profils publics maintenus par les utilisateurs pour corréler leurs comptes. Nous identifions quatre propriétés importantes - la disponibilité, la cohérence, la non-impersonabilite, et la discriminabilité (ACID) - pour évaluer la qualité de différents attributs pour corréler des comptes. On peut corréler un grand nombre de comptes parce-que les utilisateurs maintiennent les mêmes noms et d'autres informations personnelles à travers des différents réseaux sociaux. Pourtant, il reste difficile d'obtenir une précision suffisant pour utiliser les corrélations dans la pratique à cause de la grandeur de réseaux sociaux réels. Nous développons des schémas qui obtiennent des faible taux d'erreur même lorsqu'elles sont appliquées dans les réseaux avec des millions d'utilisateurs. Ensuite, nous montrons que nous pouvons corréler les comptes d'utilisateurs même si nous exploitons que leur activité sur un les réseaux sociaux. Ça sa démontre que, même si les utilisateurs maintient des profils distincts nous pouvons toutefois corréler leurs comptes. Enfin, nous montrons que, en identifiant les comptes qui correspondent à la même personne à l'intérieur d'un réseau social, nous pouvons détecter des imitateurs. / The proliferation of social networks and all the personal data that people share brings many opportunities for developing exciting new applications. At the same time, however, the availability of vast amounts of personal data raises privacy and security concerns.In this thesis, we develop methods to identify the social networks accounts of a given user. We first study how we can exploit the public profiles users maintain in different social networks to match their accounts. We identify four important properties – Availability, Consistency, non- Impersonability, and Discriminability (ACID) – to evaluate the quality of different profile attributes to match accounts. Exploiting public profiles has a good potential to match accounts because a large number of users have the same names and other personal infor- mation across different social networks. Yet, it remains challenging to achieve practically useful accuracy of matching due to the scale of real social networks. To demonstrate that matching accounts in real social networks is feasible and reliable enough to be used in practice, we focus on designing matching schemes that achieve low error rates even when applied in large-scale networks with hundreds of millions of users. Then, we show that we can still match accounts across social networks even if we only exploit what users post, i.e., their activity on a social networks. This demonstrates that, even if users are privacy conscious and maintain distinct profiles on different social networks, we can still potentially match their accounts. Finally, we show that, by identifying accounts that correspond to the same person inside a social network, we can detect impersonators.

Ces dernières années, le contenu disponible sur le Web a augmenté de manière considérable dans ce qu’on appelle communément le Web social. Pour l’utilisateur moyen, il devient de plus en plus difficile de recevoir du contenu de qualité sans se voir rapidement submergé par le flot incessant de publications. Pour les fournisseurs de service, le passage à l’échelle reste problématique. L’objectif de cette thèse est d’aboutir à une meilleure expérience utilisateur à travers la mise en place de systèmes de filtrage et de recommandation. Le filtrage consiste à offrir la possibilité à un utilisateur de ne recevoir qu’un sous ensemble des publications des comptes auxquels il est abonné. Tandis que la recommandation permet la découverte d’information à travers la suggestion de comptes à suivre sur des sujets donnés. Nous avons élaboré MicroFilter un système de filtrage passant à l’échelle capable de gérer des flux issus du Web ainsi que RecLand, un système de recommandation qui tire parti de la topologie du réseau ainsi que du contenu afin de générer des recommandations pertinentes. / In the last years, the amount of available data on the social Web has exploded. For the average user, it became hard to find quality content without being overwhelmed with publications. For service providers, the scalability of such services became a challenging task. The aim of this thesis is to achieve a better user experience by offering the filtering and recommendation features. Filtering consists to provide for a given user, the ability of receiving only a subset of the publications from the direct network. Where recommendation allows content discovery by suggesting relevant content producers on given topics. We developed MicroFilter, a scalable filtering system able to handle Web-like data flows and RecLand, a recommender system that takes advantage of the network topology as well as the content in order to provide relevant recommendations.

Avec l’avènement du numérique, il est désormais possible aux chercheurs d’amasser des grandes quantités de données et les plateformes de réseaux sociaux en ligne ne font pas exception à cela. Les sociologues, comme d’autres, se sont emparés de ces nouvelles ressources afin de poursuivre leurs enquêtes sur les modalités de l’interaction entre individus et leur impact sur la structuration de la sociabilité. Suivant cette voie, ce travail de thèse vise à l’analyse d’un grand nombre de comptes Facebook, aussi bien au travers des outils classiques de l’analyse de données que de la théorie des graphes, à laquelle des contributions méthodologiques sont apportées. Deux facteurs principaux encouragent l’étude de l’activité et de la sociabilité en ligne. D’une part, le temps important dédié à cette plateforme par de nombreux internautes justifie l’intérêt porté par les sociologues aux échanges qui s’y construisent. Par ailleurs, et contrairement à ce que l’on peut observer sur d’autre sites de réseaux sociaux en ligne, les liens entre individus sur Facebook sont proches de ceux hors-lignes. Dans un premier temps, la thèse s’évertue à démêler les multiples facettes de ce à quoi ”être sur Facebook” correspond. Distribués autour de pratiques normatives fabulées, les usages de nos enquêtés fluctuent au gré de leur appropriation ou non des composantes de l’importante variété de moyens de communication proposés par la plateforme. Ces usages, comme on le verra, sont ainsi différemment adoptés selon les catégories socioprofessionnelles et influent par ailleurs sur les modalités d’échanges et d’interactions des enquêtés avec leurs amis en ligne. Ces modalités sont également explorées dans ce travail, tout comme le rôle du conjoint et sa place dans la structure relationnelle. La seconde partie de la thèse se propose de construire une typologie de ces structures relationnelles dites égocentrées, c’est-à-dire depuis le point de vue de l’enquêté. Cette typologie des réseaux de sociabilité en ligne se base sur l’énumération de leurs sous-graphes induits, les graphlets, initialement développée par des chercheurs en bioinformatique. Cette approche offre une vision méso (entre micro et macro) des réseaux, propice à souligner des phénomènes inédits de sociologie des réseaux. A fort potentiel pluri-disciplinaire, la méthodologie graphlets elle même est également discutée et explorée. / With the digital advent, it is now possible for researchers to collect important amounts of data and online social network platforms are surely part of it. Sociologists, among others, seized those new resources to investigate over interaction modalities between individuals as well as their impact on the structure of sociability. Following this lead, this thesis work aims at analyzing a large number of Facebook accounts, through data analysis and graph theory classical tools, and to bring methodological contributions. Two main factors encourage to study Facebook social activities. On one hand, the importance of time spent on this platform by many Internet users justifies by itself the sociologists interest. On the other, and contrarily to what we observe on other social network websites, ties between individuals are similar to the ones that appear offline. First, the thesis proposes to detangle the multiple meanings that are behind the fact of ”being on Facebook”. The uses of our surveyed are not compacted in fantasized normative practices but vary depending on how they appropriate the different composers of the platform tools. These uses, as we will see it, do not concern all the socioprofessional categories in the same way and they also influence how the respondents interact with their online friends. The manuscript also explores these interactions, as well as the lover role into the relational structure. Second part of the thesis builds a typology of these relational structures. They are said as egocentred, which means that they are taken from the perspective of the respondent. This typology of social networks is based on their graphlet counts, that are the number of times each type of subnetwork appear in them. This approach offers a meso perspective (between micro and macro), that is propitious to underline some new social phenomena. With a high pluri-disciplinary potential, the graphlet methodology is also discussed and explored itself.

In online social networking sites, gaining popularity has become important. The more popular a company is, the more profits it can make. A way to measure a company's popularity is to check how many likes it has (e.g., the company's number of likes in Facebook). To instantly and artificially increase the number of likes, some companies and business people began hiring crowd workers (aka fake likers) who send likes to a targeted page and earn money. Unfortunately, little is known about characteristics of the fake likers and how to identify them. To uncover fake likers in online social networks, in this work we (i) collect profiles of fake likers and legitimate likers by using linkage and honeypot approaches, (ii) analyze characteristics of fake likers and legitimate likers, (iii) propose and develop a fake liker detection approach, and (iv) thoroughly evaluate its performance against three baseline methods and under two attack models. Our experimental results show that our cassification model significantly outperformed the baseline methods, achieving 87.1% accuracy and 0.1 false positive rate and 0.14 false negative rate.

Les réseaux sociaux ont connu une évolution dramatique et ont été utilisés comme des moyens pour exercer plusieurs activités. En fait, via les réseaux sociaux, les utilisateurs peuvent découvrir, gérer et partager leurs expériences et avis en ligne. Cependant, la nature ouverte et décentralisée des réseaux sociaux les rend vulnérables à l'apparition des utilisateurs malveillants. Par conséquent, les utilisateurs éventuels peuvent faire face à plusieurs de problèmes liés à la confiance. Ainsi, une évaluation de confiance effective et efficace est très importante pour la prise de décisions par ces utilisateurs. En effet, elle leur fournit des informations précieuses leur permettant de faire la différence entre ceux dignes et indignes de confiance. Cette thèse a pour but de fournir des méthodes de gestion de confiance et de réputation des utilisateurs des réseaux sociaux efficaces et qui peuvent être présentées par les quatre contributions suivantes. La première contribution présente une complexe extraction des contextes et des intérêts des utilisateurs, où les informations contextuelles sociales complexes sont prises en compte, reflétant mieux les réseaux sociaux. De plus, nous proposons un enrichissement de l'ontologie Dbpedia par des concepts de folksonomies.Ensuite, nous proposons une approche de gestion de la confiance, intitulée IRIS, permettant la génération du réseau de confiance et le calcul de la confiance directe. Cette approche considère les activités sociales des utilisateurs incluant leurs relations sociales, préférences et interactions.La troisième contribution de cette thèse est la gestion de transitivité de confiance dans les réseaux sociaux. En fait, c'est nécessaire et significatif d'évaluer la confiance entre deux participants n’ayant pas des interactions directes. Nous proposons ainsi, un modèle d'inférence de confiance, appelé TISON, pour évaluer la confiance indirecte dans les réseaux sociaux.La quatrième contribution de cette thèse consiste à gérer la réputation des utilisateurs des réseaux sociaux. Pour ce faire, nous proposons deux nouveaux algorithmes. Nous présentons un nouvel algorithme exclusif pour la classification des utilisateurs basés sur leurs réputations, appelé le RePC. De plus, nous proposons un deuxième algorithme, FCR, qui présente une extension floue de RePC. Pour les approches proposées, nous avons conduits différentes expérimentations sur des ensembles de données réels ou aléatoires. Les résultats expérimentaux ont démontré que nos algorithmes proposés produisent de meilleurs résultats, en termes de qualité des résultats livrés et d’efficacité, par rapport à différentes approches introduites dans littérature / Online Social Networks (OSNs) have known a dramatic increase and they have been used as means for a rich variety of activities. In fact, within OSNs, usersare able to discover, extend, manage, and leverage their experiences and opinionsonline. However, the open and decentralized nature of the OSNs makes themvulnerable to the appearance of malicious users. Therefore, prospective users facemany problems related to trust. Thus, effective and efficient trust evaluation isvery crucial for users’ decision-making. It provides valuable information to OSNsusers, enabling them to make difference between trustworthy and untrustworthyones. This thesis aims to provide effective and efficient trust and reputationmanagement methods to evaluate trust and reputation of OSNs users, which canbe divided into the following four contributions.The first contribution presents a complex trust-oriented users’ contexts andinterests extraction, where the complex social contextual information is taken intoaccount in modelling, better reflecting the social networks in reality. In addition,we propose an enrichment of the Dbpedia ontology from conceptualizations offolksonomies.We second propose the IRIS (Interactions, Relationship types and Interest Similarity)trust management approach allowing the generation of the trust networkand the computation of direct trust. This model considers social activities of usersincluding their social relationships, preferences and interactions. The intentionhere is to form a solid basis for the reputation and indirect trust models.The third contribution of this thesis is trust inference in OSNs. In fact, it isnecessary and significant to evaluate the trust between two participants whomhave not direct interactions. We propose a trust inference model called TISON(Trust Inference in Social Networks) to evaluate Trust Inference within OSNs.The fourth contribution of this thesis consists on the reputation managementin OSNs. To manage reputation, we proposed two new algorithms. We introducea new exclusive algorithm for clustering users based on reputation, called RepC,based on trust network. In addition, we propose a second algorithm, FCR, whichis a fuzzy extension of RepC.For the proposed approaches, extensive experiments have been conducted onreal or random datasets. The experimental results have demonstrated that ourproposed algorithms generate better results, in terms of the utility of delivered results and efficiency, than do the pioneering approaches of the literature