962 research outputs found

    Open challenges in relationship-based privacy mechanisms for social network services

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    [EN] Social networking services (SNSs) such as Facebook or Twitter have experienced an explosive growth during the few past years. Millions of users have created their profiles on these services because they experience great benefits in terms of friendship. SNSs can help people to maintain their friendships, organize their social lives, start new friendships, or meet others that share their hobbies and interests. However, all these benefits can be eclipsed by the privacy hazards that affect people in SNSs. People expose intimate information of their lives on SNSs, and this information affects the way others think about them. It is crucial that users be able to control how their information is distributed through the SNSs and decide who can access it. This paper presents a list of privacy threats that can affect SNS users, and what requirements privacy mechanisms should fulfill to prevent this threats. Then, we review current approaches and analyze to what extent they cover the requirementsThis article has been developed as a result of a mobility stay funded by the Erasmus Mundus Programme of the European Comission under the Transatlantic Partnership for Excellence in Engineering-TEE Project.López Fogués, R.; Such Aparicio, JM.; Espinosa Minguet, AR.; García-Fornes, A. (2015). Open challenges in relationship-based privacy mechanisms for social network services. International Journal of Human-Computer Interaction. 31(5):350-370. doi:10.1080/10447318.2014.1001300S35037031

    Enhancing Privacy Management on Social Network Services

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    Tesis por compendioIn the recent years, social network services, such as Facebook or LinkedIn, have experienced an exponential growth. People enjoy their functionalities, such as sharing photos, finding friends, looking for jobs, and in general, they appreciate the social benefits that social networks provide. However, as using social network has become routine for many people, privacy breaches that may occur in social network services have increased users' concerns. For example, it is easy to find news about people being fired because of something they shared on a social network. To enable people define their privacy settings, service providers employ simple access controls which usually rely exclusively on lists or circles of friends. Although these access controls are easy to configure by average users, research literature points out that they are lacking elements, such as tie strength, that play a key role when users decide what to share and with whom. Additionally, despite the simplicity of current access controls, research on privacy on social media reports that people still struggle to effectively control how their information flows on these services. To provide users with a more robust privacy framework, related literature proposes a new paradigm for access controls based on relationships. In contrast to traditional access controls where permissions are granted based on users and their roles, this paradigm employs social elements such as the relationship between the information owner and potential viewers (e.g., only my siblings can see this photo). Access controls that follow this paradigm provide users with mechanisms for disclosure control that represent more naturally how humans reason about privacy. Furthermore, these access controls can deal with specific issues that social network services present. Specifically, users often share information that concerns many people, especially other members of the social network. In such situations, two or more people can have conflicting privacy preferences; thus, an appropriate sharing policy may not be apparent. These situations are usually identified as multiuser privacy scenarios. Since relationship based access controls are complex for the average social network user, service providers have not adopted them. Therefore, to enable the implementation of such access controls in current social networks, tools and mechanisms that facilitate their use must be provided. To that aim, this thesis makes five contributions: (1) a review of related research on privacy management on social networks that identifies pressing challenges in the field, (2) BFF, a tool for eliciting automatically tie strength and user communities, (3) a new access control that employs communities, individual identifiers, tie strength, and content tags, (4) a novel model for representing and reasoning about multiuser privacy scenarios, employing three types of features: contextual factors, user preferences, and user arguments; and, (5) Muppet, a tool that recommends sharing policies in multiuser privacy scenarios.En los últimos años, los servicios de redes sociales, como Facebook o LinkedIn, han experimentado un crecimiento exponencial. Los usuarios valoran positivamente sus muchas funcionalidades tales como compartir fotos, o búsqueda de amigos y trabajo. En general, los usuarios aprecian los beneficios que las redes sociales les aportan. Sin embargo, mientras el uso de redes sociales se ha convertido en rutina para mucha gente, brechas de privacidad que pueden ocurrir en redes sociales han aumentado los recelos de los usuarios. Por ejemplo, es sencillo encontrar en las noticias casos sobre personas que han perdido su empleo debido a algo que compartieron en una red social. Para facilitar la definición de los ajustes de privacidad, los proveedores de servicios emplean controles de acceso sencillos que normalmente se basan, de forma exclusiva, en listas o círculos de amigos. Aunque estos controles de acceso son fáciles de configurar por un usuario medio, investigaciones recientes indican que éstos carecen de elementos tales como la intensidad de los vínculos personales, que juegan un papel clave en cómo los usuarios deciden qué compartir y con quién. Además, a pesar de la simplicidad de los controles de acceso, investigaciones sobre privacidad en redes sociales señalan que los usuarios han de esforzarse para controlar de forma efectiva como su información fluye en estos servicios. Para ofrecer a los usuarios un marco de privacidad más robusto, trabajos recientes proponen un nuevo paradigma para controles de acceso basado en relaciones. A diferencia de los controles de acceso tradicionales donde los permisos se otorgan en base a usuarios y sus roles, este paradigma emplea elementos sociales como la relación entre el propietario de la información y su audiencia potencial (por ejemplo, sólo mis hermanos pueden ver la foto). Los controles de acceso que siguen este paradigma ofrecen a los usuarios mecanismos para el control de la privacidad que representan de una forma más natural como los humanos razonan sobre cuestiones de privacidad. Además, estos controles de acceso pueden lidiar con problemáticas específicas que presentan las redes sociales. Específicamente, los usuarios comparten de forma habitual información que atañe a muchas personas, especialmente a otros miembros de la red social. En tales situaciones, dos o más personas pueden tener preferencias de privacidad que entran en conflicto. Cuando esto ocurre, no hay una configuración correcta de privacidad que sea evidente. Estas situaciones son normalmente identificadas como escenarios de privacidad multiusuario. Dado que los controles de acceso basados en relaciones son complejos para el usuario promedio de redes sociales, los proveedores de servicios no los han adoptado. Por lo tanto, para permitir la implementación de tales controles de acceso en redes sociales actuales, es necesario que se ofrezcan herramientas y mecanismos que faciliten su uso. En este sentido, esta tesis presenta cinco contribuciones: (1) una revisión del estado del arte en manejo de privacidad en redes sociales que permite identificar los retos más importantes en el campo, (2) BFF, una herramienta para obtener automáticamente la intensidad de los vínculos personales y las comunidades de usuarios, (3) un nuevo control de acceso que emplea comunidades, identificadores individuales, la intensidad de los vínculos personales, y etiquetas de contenido, (4) un modelo novedoso para representar y razonar sobre escenarios de privacidad multiusario que emplea tres tipos de características: factores contextuales, preferencias de usuario, y argumentos de usuario; y, (5) Muppet, una herramienta que recomienda configuraciones de privacidad en escenarios de privacidad multiusuario.En els darrers anys, els servicis de xarxes socials, com Facebook o LinkedIn, han experimentat un creixement exponencial. Els usuaris valoren positivament les seues variades funcionalitats com la compartició de fotos o la cerca d'amics i treball. En general, els usuaris aprecien els beneficis que les xarxes socials els aporten. No obstant això, mentre l'ús de les xarxes socials s'ha convertit en rutina per a molta gent, bretxes de privacitat que poden ocórrer en xarxes socials han augmentat els recels dels usuaris. Per exemple, és senzill trobar notícies sobre persones que han perdut el seu treball per alguna cosa que compartiren a una xarxa social. Per facilitar la definició dels ajustos de privacitat, els proveïdors de servicis empren controls d'accés senzills que normalment es basen, de forma exclusiva, en llistes o cercles d'amics. Encara que aquests controls d'accés són fàcils d'emprar per a un usuari mitjà, investigacions recents indiquen que aquests manquen elements com la força dels vincles personals, que juguen un paper clau en com els usuaris decideixen què compartir i amb qui. A més a més, malgrat la simplicitat dels controls d'accés, investigacions sobre privacitat en xarxes socials revelen que els usuaris han d'esforçar-se per a controlar de forma efectiva com fluix la seua informació en aquests servicis. Per a oferir als usuaris un marc de privacitat més robust, treballs recents proposen un nou paradigma per a controls d'accés basat en relacions. A diferència dels controls d'accés tradicionals on els permisos s'atorguen segons usuaris i els seus rols, aquest paradigma empra elements socials com la relació entre el propietari de la informació i la seua audiència potencial (per exemple, sols els meus germans poden veure aquesta foto). Els controls d'accés que segueixen aquest paradigma ofereixen als usuaris mecanismes per al control de la privacitat que representen d'una forma més natural com els humans raonen sobre la privacitat. A més a més, aquests controls d'accés poden resoldre problemàtiques específiques que presenten les xarxes socials. Específicament, els usuaris comparteixen de forma habitual informació que concerneix moltes persones, especialment a altres membres de la xarxa social. En aquestes situacions, dues o més persones poden tindre preferències de privacitat que entren en conflicte. Quan açò ocorre, no hi ha una configuració de privacitat correcta que siga evident. Aquestes situacions són normalment identificades com escenaris de privacitat multiusari. Donat que els controls d'accés basats en relacions són complexos per a l'usuari mitjà de xarxes socials, els proveïdors de servicis no els han adoptat. Per tant, per a permetre la implementació d'aquests controls d'accés en xarxes socials actuals, és necessari oferir ferramentes i mecanismes que faciliten el seu ús. En aquest sentit, aquesta tesi presenta cinc contribucions: (1) una revisió de l'estat de l'art en maneig de privacitat en xarxes socials que permet identificar els reptes més importants en el camp, (2) BFF, una ferramenta per a obtenir automàticament la força dels vincles personals i les comunitats d'usuaris, (3) un nou control d'accés que empra comunitats, identificadors individuals, força dels vincles personals, i etiquetes de contingut, (4) un model nou per a representar i raonar sobre escenaris de privacitat multiusari que empra tres tipus de característiques: factors contextuals, preferències d'usuari, i arguments d'usuaris; i, (5) Muppet, una ferramenta que recomana configuracions de privacitat en escenaris de privacitat multiusuari.López Fogués, R. (2017). Enhancing Privacy Management on Social Network Services [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/85978TESISCompendi

    Exploratory Browsing

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    In recent years the digital media has influenced many areas of our life. The transition from analogue to digital has substantially changed our ways of dealing with media collections. Today‟s interfaces for managing digital media mainly offer fixed linear models corresponding to the underlying technical concepts (folders, events, albums, etc.), or the metaphors borrowed from the analogue counterparts (e.g., stacks, film rolls). However, people‟s mental interpretations of their media collections often go beyond the scope of linear scan. Besides explicit search with specific goals, current interfaces can not sufficiently support the explorative and often non-linear behavior. This dissertation presents an exploration of interface design to enhance the browsing experience with media collections. The main outcome of this thesis is a new model of Exploratory Browsing to guide the design of interfaces to support the full range of browsing activities, especially the Exploratory Browsing. We define Exploratory Browsing as the behavior when the user is uncertain about her or his targets and needs to discover areas of interest (exploratory), in which she or he can explore in detail and possibly find some acceptable items (browsing). According to the browsing objectives, we group browsing activities into three categories: Search Browsing, General Purpose Browsing and Serendipitous Browsing. In the context of this thesis, Exploratory Browsing refers to the latter two browsing activities, which goes beyond explicit search with specific objectives. We systematically explore the design space of interfaces to support the Exploratory Browsing experience. Applying the methodology of User-Centered Design, we develop eight prototypes, covering two main usage contexts of browsing with personal collections and in online communities. The main studied media types are photographs and music. The main contribution of this thesis lies in deepening the understanding of how people‟s exploratory behavior has an impact on the interface design. This thesis contributes to the field of interface design for media collections in several aspects. With the goal to inform the interface design to support the Exploratory Browsing experience with media collections, we present a model of Exploratory Browsing, covering the full range of exploratory activities around media collections. We investigate this model in different usage contexts and develop eight prototypes. The substantial implications gathered during the development and evaluation of these prototypes inform the further refinement of our model: We uncover the underlying transitional relations between browsing activities and discover several stimulators to encourage a fluid and effective activity transition. Based on this model, we propose a catalogue of general interface characteristics, and employ this catalogue as criteria to analyze the effectiveness of our prototypes. We also present several general suggestions for designing interfaces for media collections

    Multi-view Latent Factor Models for Recommender Systems

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    Human Resources Recommender system based on discrete variables

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceNatural Language Processing and Understanding has become one of the most exciting and challenging fields in the area of Artificial Intelligence and Machine Learning. With the rapidly changing business environment and surroundings, the importance of having the data transformed in such a way that makes it easy to interpret is the greatest competitive advantage a company can have. Having said this, the purpose of this thesis dissertation is to implement a recommender system for the Human Resources department in a company that will aid the decision-making process of filling a specific job position with the right candidate. The recommender system fill be fed with applicants, each being represented by their skills, and will produce a subset of most adequate candidates given a job position. This work uses StarSpace, a novelty neural embedding model, whose aim is to represent entities in a common vectorial space and further perform similarity measures amongst them
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