Bibliographies: 'Users - Social recognition' – Grafiati (2025)

Abstract:

The billions of users all over the world are spending online social network, such as Twitter, Facebook, Tumbler and LinkedIn. The flaws in this social media may indications to abuse user’s information and execute an attack of identity cloning. In this work mainly focuses, a new method for hiding data to hide precise details in profile pictures to learn botnets and fake profiles. In this paper, presents an ordering and investigation of recognition mechanisms of genetic copy attacks on online network of social, purely established on attribute likeness, friend network likeness, and profile inquiry for a time interval and record of Internet Protocol sequences. This work, proposals an algorithm for transform discrete wavelet for hiding the data. So, the system can prevent the replica attacks and offer the whole user data privacy protective. Similarly, when users upload the profile image or photos it would be first watermarked and then updated. Java static watermarking systems and algorithms is been used for watermarking procedure. Here tracking any fake users updating the same profile picture given easier and tracking their IP address also became easier. Also, our system raises certain features which can be investigated to the users through process of registration. Thus, providing secure authentication. Hence avoiding clone attacks in social media became easier.

Abstract:

The mobile phone is no longer only a communication device, but also a powerful environmental sensing unit that can monitor a user’s ambient context. Mobile users take their devices with them everywhere which increases the availability of persons’ traces. Extracting and analyzing knowledge from these traces represent a strong support for several applications domains, ranging from traffic management to advertisement and social studies. However, the limited battery capacity of mobile devices represents a big hurdle for context detection, no matter how useful the service may be. We present a novel approach to online recognizing users’ outdoor activities without depleting the mobile resources. We associate the places visited by individuals during their movements with meaningful human activities using a novel algorithm that clusters incrementally user’s moves into different types of activities. To optimize the battery consumption, the algorithm behaves variably on the basis of users’ behaviors and the remaining battery level. Studies using real GPS records from two big datasets demonstrate that the proposal is effective and is capable of inferring human activities without draining the phone resources.

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Abstract Advances in deep learning have made face recognition technologies pervasive. While useful to social media platforms and users, this technology carries significant privacy threats. Coupled with the abundant information they have about users, service providers can associate users with social interactions, visited places, activities, and preferences–some of which the user may not want to share. Additionally, facial recognition models used by various agencies are trained by data scraped from social media platforms. Existing approaches to mitigate associated privacy risks result in an imbalanced trade-off between privacy and utility. In this paper, we address this trade-off by proposing Face-Off, a privacy-preserving framework that introduces strategic perturbations to images of the user’s face to prevent it from being correctly recognized. To realize Face-Off, we overcome a set of challenges related to the black-box nature of commercial face recognition services, and the scarcity of literature for adversarial attacks on metric networks. We implement and evaluate Face-Off to find that it deceives three commercial face recognition services from Microsoft, Amazon, and Face++. Our user study with 423 participants further shows that the perturbations come at an acceptable cost for the users.

Abstract:

Background: Long-term opiate users experience pervasive social difficulties, but there has been surprisingly limited research focused on social-cognitive functioning in this population. Aim: The aim of this study was to investigate whether three important aspects of social cognition (facial emotion recognition, theory of mind (ToM) and rapid facial mimicry) differ between long-term opiate users and healthy controls. Methods: The participants were 25 long-term opiate users who were enrolled in opiate substitution programmes, and 25 healthy controls. Facial emotion recognition accuracy was indexed by responses to 60 photographs of faces depicting the six basic emotions (happiness, sadness, anger, fear, surprise and disgust). ToM was assessed using the Reading the Mind in the Eyes task, which requires participants to infer mental states of others from partial facial cues. Rapid facial mimicry was assessed by recording activity in the zygomaticus major and corrugator supercilii muscle regions while participants passively viewed images of happy and angry facial expressions. Results: Relative to the control group, the opiate user group exhibited deficits in both facial emotion recognition and ToM. Moreover, only control participants exhibited typical rapid facial mimicry responses to happy facial expressions. Conclusions: These data indicate that long-term opiate users exhibit abnormalities in three distinct areas of social-cognitive processing, pointing to the need for additional work to establish how social-cognitive functioning relates to functional outcomes in this group. Such work may ultimately inform the development of interventions aimed at improving treatment outcomes for long-term opiate users.

Abstract:

Online social networks are of essence, as a tool for communication, for millions of people in their real world. However, online social networks also serve an arena of information war. One tool for infowar is bots, which are thought of as software designed to simulate the real user’s behaviour in online social networks.The paper objective is to develop a model for recognition of bots in online social networks. To develop this model, a machine-learning algorithm “Random Forest” was used. Since implementation of machine-learning algorithms requires the maximum data amount, the Twitter online social network was used to solve the problem of bot recognition. This online social network is regularly used in many studies on the recognition of bots.For learning and testing the Random Forest algorithm, a Twitter account dataset was used, which involved above 3,000 users and over 6,000 bots. While learning and testing the Random Forest algorithm, the optimal hyper-parameters of the algorithm were determined at which the highest value of the F1 metric was reached. As a programming language that allowed the above actions to be implemented, was chosen Python, which is frequently used in solving problems related to machine learning.To compare the developed model with the other authors’ models, testing was based on the two Twitter account datasets, which involved as many as half of bots and half of real users. As a result of testing on these datasets, F1-metrics of 0.973 and 0.923 were obtained. The obtained F1-metric values are quite high as compared with the papers of other authors.As a result, in this paper a model of high accuracy rates was obtained that can recognize bots in the Twitter online social network.

Abstract:

Abstract Purpose In this paper, we describe how gender recognition on Twitter can be used as an intelligent business tool to determine the privacy concerns among users, and ultimately offer a more personalized service for customers who are more likely to respond positively to targeted advertisements. Design/methodology/approach We worked with two different data sets to examine whether Twitter users’ gender, inferred from the first name of the account and the profile description, correlates with the privacy setting of the account. We also used a set of features including the inferred gender of Twitter users to develop classifiers that predict user privacy settings. Findings We found that the inferred gender of Twitter users correlates with the account’s privacy setting. Specifically, females tend to be more privacy concerned than males. Users whose gender cannot be inferred from their provided first names tend to be more privacy concerned. In addition, our classification performance suggests that inferred gender can be used as an indicator of the user’s privacy preference. Research limitations It is known that not all twitter accounts are real user accounts, and social bots tweet as well. A major limitation of our study is the lack of consideration of social bots in the data. In our study, this implies that at least some percentage of the undefined accounts, that is, accounts that had names non-existent in the name dictionary, are social bots. It will be interesting to explore the privacy setting of social bots in the Twitter space. Practical implications Companies are investing large amounts of money in business intelligence tools that allow them to know the preferences of their consumers. Due to the large number of consumers around the world, it is very difficult for companies to have direct communication with each customer to anticipate market changes. For this reason, the social network Twitter has gained relevance as one ideal tool for information extraction. On the other hand, users’ privacy preference needs to be considered when companies consider leveraging their publicly available data. This paper suggests that gender recognition of Twitter users, based on Twitter users’ provided first names and their profile descriptions, can be used to infer the users’ privacy preference. Originality/value This study explored a new way of inferring Twitter user’s gender, that is, to recognize the user’s gender based on the provided first name and the user’s profile description. The potential of this information for predicting the user’s privacy preference is explored.

Abstract:

Like most new technologies, virtual reality (VR) has been the subject of a great deal of idealization. This paper both debunks that idealization by discussing some problems that certain types of VR could cause and emphasizes how other types of VR could bring the technology closer to its ideal. Virtual reality is divided into four types: social (there are real other people to interact with), nonsocial (other interactants are simulations of people), creative (users can create elements in the virtual environment), and noncreative (users interact with a fixed environment created for them). Nonsocial VR may cause problems by making it difficult for children and adolescents to learn social skills. Noncreative VR is problematic because it places limits on users' creativity and freedom. Engineers developing VR technology are encouraged to develop social and creative VR.

Abstract:

Online social media (OSN) has witnessed a significant growth over past decade. Millions of people now share their thoughts, emotions, preferences, opinions and aesthetic information in the form of images, videos, music, texts, blogs and emoticons. Recently, due to existence of person specific traits in media data, researchers started to investigate such traits with the goal of biometric pattern analysis and recognition. Until now, gender recognition from image aesthetics has not been explored in the biometric community. In this paper, the authors present an authentic model for gender recognition, based on the discriminating visual features found in user favorite images. They validate the model on a publicly shared database consisting of 24,000 images provided by 120 Flickr (image based OSN) users. The authors propose the method based on the mixture of experts model to estimate the discriminating hyperplane from 56 dimensional aesthetic feature space. The experts are based on k-nearest neighbor, support vector machine and decision tree methods. To improve the model accuracy, they apply a systematic feature selection using statistical two sampled t-test. Moreover, the authors provide statistical feature analysis with graph visualization to show discriminating behavior between male and female for each feature. The proposed method achieves 77% accuracy in predicting gender, which is 5% better than recently reported results.

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In this work an affective computing approach is used to study the human-robot interaction using a social robot to validate facial expressions in the wild. Our global goal is to evaluate that a social robot can be used to interact in a convincing manner with human users to recognize their potential emotions through facial expressions, contextual cues and bio-signals. In particular, this work is focused on analyzing facial expression. A social robot is used to validate a pre-trained convolutional neural network (CNN) which recognizes facial expressions. Facial expression recognition plays an important role in recognizing and understanding human emotion by robots. Robots equipped with expression recognition capabilities can also be a useful tool to get feedback from the users. The designed experiment allows evaluating a trained neural network in facial expressions using a social robot in a real environment. In this paper a comparison between the CNN accuracy and human experts is performed, in addition to analyze the interaction, attention and difficulty to perform a particular expression by 29 non-expert users. In the experiment, the robot leads the users to perform different facial expressions in motivating and entertaining way. At the end of the experiment, the users are quizzed about their experience with the robot. Finally, a set of experts and the CNN classify the expressions. The obtained results allow affirming that the use of social robot is an adequate interaction paradigm for the evaluation on facial expression.

Abstract:

Facial tracking technologies have been incorporated in digital cameras for many years, and are offered to users of social networks such as Facebook to facilitate and automatize tagging (the process of recognizing one’s face in a picture and associating it with a user’s profile) and image sharing. Nevertheless, in recent times, facial recognition technologies seem to have taken a new turn, and from the simple recognition of faces with cameras and social networks they have become embedded in mainstream security technologies as much as in entertaining ‘face swap’ apps, transforming the social and cultural implications of the selfie. This paper examines the political implications of new technologies for facial recognition, and proposes a new type of selfie aesthetic characterized by new forms of human and machinic agency. The paper argues that when the selfie becomes mediated by new tracking technologies for security system and entertainment based on face-recognition algorithms, the selfie becomes an ‘Algorithmic Facial Image’.

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Submitted by Filipe dos Santos (fsantos@pucsp.br) on 2018-04-18T11:33:51ZNo. of bitstreams: 1Cláudia Oliveira Sant_Anna.pdf: 2450935 bytes, checksum: c9042b907824925ac174ca0dea9b4ac3 (MD5)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES
The present dissertation has as objective to know and understand the perception of the users related to their recognition in the attention offered by a Social Assistance Service. It is the approach related to the institutional reception service, understanding the manner the social recognition expressions are made in the trajectory of attention to users, knowing the expressions of social deprotection which leads them to access a special social protection service of high complexity in the social assistance, as well identifying with families the acquisitions recognized as answers to their needs. The analytical route performed in this study demanded deepening about the scope of an institutional reception service to children from their historical evolution in Brazil and particularly the impact of legalization of social rights to the Brazilian people viable through the Federal Constitution of 1988 against the objective of Child and Adolescent Statute (ECA) and the Social Assistance Unique System (SUAS). In the course of this research, with the support of several authors it was possible to show the event which occurred historically in the legal area in overcome the attention to children in Brazil in the field of charity, favor and goodwill, supported by the value judgement for the perspective of attentions in the social right condition. To the interviews and field surveys were selected five families who had as reason of institutional reception of children the negligence or the abandonment. The study plunged in the relationship among the family, the child and the service, and being synthesized in three moments: the triggering situation of the reception: reason, complainant, procedure of the tutelary council and the judge, link with some social assistance service; the time of attention to the child in the reception and the manner of relation to the family made by the service and verified in the file records and the users’ speeches highlighting the records on: the attentions supported by the service and its direct repercussion in the life of the children, teenagers and families; the relation with the families and of their access to the public attentions and services which they would be entitled to; the ways in which social security was ensured to the children and teenagers; of activies that the children had the opportunity to experience during the institutional reception; and finally the moment of post-dismissal of the child of the reception service. It is a qualitative research whose essence was the quest to listen to users, which represents the most important step in this study, which allowed to know the meaning attributed by users to the attention of an institutional reception service
A presente dissertação tem como objetivo conhecer e compreender a percepção e as expressões dos usuários quanto ao seu reconhecimento nas atenções oferecidas por um serviço socioassistencial. Trata-se, em especial, da abordagem em relação ao serviço de acolhimento institucional, compreendendo-se o modo como as expressões de reconhecimento social são construídas na trajetória de atenção aos usuários, conhecendo as expressões de desproteção social que os levaram a acessar um serviço de proteção social especial de alta complexidade na assistência social, bem como identificando junto às famílias as aquisições que são reconhecidas como respostas às suas necessidades. O percurso analítico realizado neste estudo demandou aprofundamento sobre o escopo de um serviço de acolhimento institucional para crianças a partir dos traços de sua evolução histórica no Brasil, e, particularmente, o que diz respeito ao impacto da legalização de direitos sociais aos brasileiros, viabilizada por meio da Constituição Federal de 1988, face ao objeto do Estatuto da Criança e do Adolescente (ECA) e do Sistema Único de Assistência Social (SUAS). No decorrer da pesquisa, com o respaldo de diversos autores, foi possível mostrar a passagem que ocorreu historicamente no campo legal em superar a atenção às crianças no Brasil do âmbito da caridade, favor e benemerência, respaldado no juízo de valor, para uma perspectiva das atenções na condição de direito social. Para as entrevistas e pesquisa de campo, foram selecionadas 05 (cinco) famílias que tiveram como motivo de acolhimento institucional das crianças a negligência ou o abandono. O estudo mergulhou na relação entre a família, a criança e o serviço, sendo sintetizado em três momentos, quais sejam: a situação desencadeante do acolhimento - motivo, autor de queixa, procedimento do Conselho Tutelar e do Juiz, vínculo com algum serviço socioassistencial; o tempo de atenção da criança no acolhimento e o modo de relação com a família, construída pelo serviço e constatada nos registros dos prontuários e nas narrativas dos usuários, destacando-se as menções sobre as atenções prestadas pelo serviço e sua repercussão direta na vida das crianças, adolescentes e famílias, a relação com as famílias e o acesso destas aos demais serviços e atenções públicas que lhes seriam de direito, os modos pelos quais foi garantida a segurança de convívio para as crianças e adolescentes, as atividades que as crianças tiveram a oportunidade de vivenciar no período de acolhimento institucional; e, por fim, o momento atual pós-desligamento da criança do serviço de acolhimento. Trata-se de uma pesquisa qualitativa, que teve em sua essência a busca por ouvir os usuários, o que representa o passo mais importante deste estudo, ou seja, o de possibilitar conhecer o significado atribuído pelos usuários da atenção de um serviço de acolhimento institucional

Abstract:

Previous research shows that people with severe disabilities often are neglected in the work of enhancing user participation. It is shown that even though professionals increase the possibility for user participation in their work, it is not necessary that the users receive it. This study aims to show how professionals working for people with disabilities applies user participation in their everyday work. We used a qualitative exploratory method and interviewed ten social workers within service administration and supportive housing, located at three different municipalities in the region of Stockholm. Using Shier’s participation model in combination with theory of recognition we got similar results as previous research. The social workers have a great intention in enhancing user’s participation in their work, though organizational structures stand in their way. That drives them to use what is known as “silent knowledge”, a combination of their personality, previous experience and their ingenuity.

Abstract:

As the amount of computer mediated information (e.g., emails, documents, multi-media) we need to process grows, our need to rapidly sort, organize and store electronic information likewise increases. In order to store information effectively, we must find ways to sort through it and organize it in a manner that facilitates efficient retrieval. The instantaneous and emergent nature of communications across networks like Twitter makes them suitable for discussing events (e.g., natural disasters) that are amorphous and prone to rapid changes. It can be difficult for an individual human to filter through and organize the large amounts of information that can pass through these types of social networks when events are unfolding rapidly. A common feature of social networks is the images (e.g., human faces, inanimate objects) that are often used by those who send messages across these networks. Humans have a particularly strong ability to recognize and differentiate between human Faces. This effect may also extend to recalling information associated with each human Face. This study investigated the difference between human Face images, non-human Face images and alphanumeric labels as retrieval cues under different levels of Task Load. Participants were required to recall key pieces of event information as they emerged from a Twitter-style message feed during a simulated natural disaster. A counter-balanced within-subjects design was used for this experiment. Participants were exposed to low, medium and high Task Load while responding to five different types of recall cues: (1) Nickname, (2) Non-Face, (3) Non-Face & Nickname, (4) Face and (5) Face & Nickname. The task required participants to organize information regarding emergencies (e.g., car accidents) from a Twitter-style message feed. The messages reported various events such as fires occurring around a fictional city. Each message was associated with a different recall cue type, depending on the experimental condition. Following the task, participants were asked to recall the information associated with one of the cues they worked with during the task. Results indicate that under medium and high Task Load, both Non-Face and Face retrieval cues increased recall performance over Nickname alone with Non-Faces resulting in the highest mean recall scores. When comparing medium to high Task Load: Face & Nickname and Non-Face significantly outperformed the Face condition. The performance in Non-Face & Nickname was significantly better than Face & Nickname. No significant difference was found between Non-Faces and Non-Faces & Nickname. Subjective Task Load scores indicate that participants experienced lower mental workload when using Non-Face cues than using Nickname or Face cues. Generally, these results indicate that under medium and high Task Load levels, images outperformed alphanumeric nicknames, Non-Face images outperformed Face images, and combining alphanumeric nicknames with images may have offered a significant performance advantage only when the image is that of a Face. Both theoretical and practical design implications are provided from these findings.
Ph.D.
Doctorate
Industrial Engineering and Management Systems
Engineering and Computer Science
Industrial Engineering

Abstract:

Våld mot kvinnor är ett allvarligt samhällsproblem och enligt socialtjänstlagen skall dessa kvinnor särskilt beaktas. I den tidigare forskning vi har tagit del av finns det bristande underlag kring vilka insatser som våldsutsatta kvinnor är i behov av. Det finns även brist på forskning som undersöker kvinnornas egna upplevelser av de insatser som erbjuds. Syftet med vår studie är att genom kvalitativa intervjuer med kvinnor som varit utsatta för våld skapa en ökad förståelse för vilken betydelse det har haft för dem att delta i en gruppverksamhet genom att lyfta kvinnornas subjektiva upplevelser. Vi har använt oss av semistrukturerade intervjuer och intervjuat fyra kvinnor som har deltagit i en gruppverksamhet. Vi hoppas att vår studie kan lyfta våldsutsatta kvinnors upplevelser av att delta i en gruppverksamhet ur ett brukarperspektiv då vi upplever att detta saknas i tidigare forskning. Vår studie har en abduktiv ansats vilket innebär att vi inte utgått från teori när vi formulerat forskningsfrågan utan i stället valt en teori kring erkännande efter att vi började bearbeta vårt resultat. Vårt intervjumaterial har analyserats med hjälp av tidigare forskning på området och Axel Honneths teori om erkännande. I vår studie kom vi fram till att kvinnorna upplevde gruppen som lyhörd och förstående. De upplevde gruppen som trygg i och med att det var en kvinnogrupp där alla hade liknande erfarenhet. Detta bidrog även till att de kände sig förstådda och mindre ensamma om sin situation. Kvinnorna uppgav även att det fått ökad förståelse för sig själva och det som skett och att denna förståelse varit viktig för att kunna bearbeta och läka från sina erfarenheter. Vi kan konstatera att våldsutsatta kvinnor är en heterogen grupp med skiftande behov. Vissa hade haft nytta av ytterligare insatser både innan och efter gruppen.

Abstract:

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O presente estudo discute a forma??o de Redes Sociais no cotidiano da Estrat?gia Sa?de da Fam?lia, a partir de aportes da teoria sociol?gica sobre redes, intera??es, d?diva e reconhecimento. O objetivo geral ? analisar as redes sociais locais em sa?de a partir da intera??o de usu?rios e profissionais da Estrat?gia Sa?de da Fam?lia na Unidade de Sa?de de Lig?ia, em Natal, RN. Seus objetivos espec?ficos s?o: Mapear as redes sociais locais em sa?de existentes no territ?rio adscrito; Identificar os tipos de intera??es cotidianas entre os sujeitos; Compreender a percep??o dos sujeitos sobre o processo de forma??o de redes sociais a partir das intera??es. Caracteriza-se enquanto pesquisa qualitativa explorat?ria cujos sujeitos foram profissionais e usu?rios vinculados ? referida unidade de sa?de. Para a coleta de dados foram utilizadas entrevistas individuais semiestruturadas e debates em grupos focais, estimulados pela Metodologia de An?lise de Redes do Cotidiano (MARES), pertinente para abordar a complexidade das rela??es sociais e mapear os diferentes conte?dos expressos e as formas de mobiliza??o coletiva. A an?lise dos dados foi realizada atrav?s da T?cnica de An?lise Tem?tica de Conte?do, proposta por Minayo. Os resultados foram interpretados ? luz das Teorias da D?diva (Mauss) e do Reconhecimento (Honneth). Os sujeitos visualizaram: Rede Virtual (28,20%); Rede de Aten??o ? Sa?de (25,64%); Redes de Usu?rios (17,95%); Rede Pessoal (10,26%); Conselho Comunit?rio (10,26%); Escolas (7,69%). Os participantes n?o perceberam os arranjos familiares enquanto Redes Sociais. Os tipos de intera??es sociais identificadas foram: Confronta??o/Negocia??o (41.02%); Harm?nicas (25,70%); Correlativas (17,90%); Definidas pela Organiza??o (15,38%). A forma??o de redes sociais ocorre a partir de intera??es cotidianas entre pessoas, pela articula??o insepar?vel de conte?dos e formas, catalisadas pelo contexto, experi?ncia e cogni??o, valorizando a liberdade, a expressividade e a diversidade dos parceiros de significa??o. Foram encontradas duas categorias, na percep??o dos sujeitos, sobre a forma??o de redes sociais do cotidiano: Di?logo e Encontro. Validamos e recomendamos o uso da metodologia MARES: Na forma??o, para despertar uma vis?o mais tolerante e humana de si e do outro; Na avalia??o qualitativa dos servi?os, por facilitar a reflex?o sobre a pr?tica e (re)organiza??o do processo de trabalho; Na comunidade, para estimular movimentos sociais existentes ou emergentes. A aposta no circuito da d?diva e do reconhecimento rec?proco, durante o tr?nsito nas redes sociais em sa?de, pode ser capaz de tecer uma pr?xis transformadora, pela busca e alcance de confian?a, respeito e estima, nos espa?os de encontro entre usu?rios e profissionais da Estrat?gia Sa?de da Fam?lia

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Besides standardising the daily use of ICTs, computer games have developed and transformed thecurrent global economy. Furthermore, the gaming industry has instilled new working practices, whichhave completely transformed the processes of consumption and production, yet blurred the linesbetween work and play.YouTube embodies this new economy. On the one hand, it is a site where users activelyparticipate and collaborate, creating relevant and sharable content. On the other hand, it is amainstream media company that handles ongoing tensions between professional and amateur users,who wish to attain recognition, as the level of competition increases.Since YouTube’s business model is based on the circulation of user-generated content, theremaining question is whether the user’s approach changes, as the platform evolves andinstitutionalises.An online inquiry was applied to a sample of 10 YouTube Gamers from four differentnationalities (Portuguese, American, Brazilian and Austrian) aged between 25 and 42, with theintention to analyse a YouTube Gamer’s identity, the creative and technical process of creating content,the YouTube Gaming Community, and finally, the perception each respondent had over the platform.The results of this study show that as the level of recognition increases, so does a YouTubeGamer’s need to perform better online, not just in terms of content, but also on how they presentthemselves.In addition, a YouTube Gamer’s perception of Youtube as a disseminator of viral content,negatively effects their user experience, which might lead them into searching for new onlineplatforms.
Para além de terem normalizado o uso das TIC, os jogos de computador tiveram um grande impactona economia global atual, nomeadamente na introdução de novas práticas laborais e na alteração dosprocessos de produção e consumo, o que dificultou a distinção entre trabalho e lazer.O YouTube expressa esta nova economia. Por um lado, permite aos seus utilizadoresparticiparam e colaborarem na criação de conteúdo relevante. Por outro lado, é uma corporação quelida com tensões entre profissionais e amadores, que tentam atingir reconhecimento, à medida que onível de competição aumenta.Dado que o modelo de negócio do YouTube é baseado na circulação de conteúdo gerado peloutilizador, questionou-se a abordagem dos utilizares face à institucionalização da plataforma.Um inquérito online foi realizado a uma amostra de 10 YouTube Gamers de quatro diferentesnacionalidades (portuguesa, americana, brasileira e austríaca) com as idades compreendidas entre os25 e os 42 anos, com o objetivo de analisar a identidade de um YouTube Gamer, o processo técnico ecriativo na criação de conteúdo, a comunidade gaming, e a percepção que cada inquirido têm acerca daplataforma.Os resultados demonstram que à medida que o nível de reconhecimento de um YouTubeGamer aumenta, também aumenta a sua necessidade de ter um melhor desempenho, não só em termosde conteúdo, como também na sua forma de apresentação.Ademais, a percepção de que o YouTube dissemina conteúdo viral, afecta negativamente aexperiência do YouTube Gamer, o que o fará procurar por outras plataformas.

Abstract:

This dissertation interrogates the deficit assumptions about English proficiency of skilled immigrants who were recruited by Canadian governments between the late 1990s and early 2000s. Through the lens of literacy as social practice, the eighteen-month ethnographic qualitative research explores the sequential experiences of settlement and economic integration of seven well-educated Chinese immigrant professionals. The analytical framework is built on sociocultural approaches to literacy and learning, as well as the theories of discourses and language reproduction. Using multiple data sources (observations, conversational interviews, journal and diary entries, photographs, documents, and artifacts collected in everyday lives), I document many different ways that well-educated Chinese immigrants take advantage of their language and literacy skills in English across several social domains of home, school, job market, and workplace. Examining the trans-contextual patterning of the participants’ language and literacy activities reveals that immigrant professionals use literacy as assistance in seeking, negotiating, and taking hold of resources and opportunities within certain social settings. However, my data show that their language and literacy engagements might not always generate positive consequences for social networks, job opportunities, and upward economic mobility. Close analyses of processes and outcomes of the participants’ engagements across these discursive discourses make it very clear that the monolithic assumptions of the dominant language shape and reinforce structural barriers by constraining their social participation, decision making, and learning practice, and thereby make literacy’s consequences unpredictable. The deficit model of language proficiency serves the grounds for linguistic stereotypes and economic marginalization, which produces profoundly consequential effects on immigrants’ pathways as they strive for having access to resources and opportunities in the new society. My analyses illuminate the ways that language and literacy create the complex web of discursive spaces wherein institutional agendas and personal desires are intertwined and collide in complex ways that constitute conditions and processes of social and economic mobility of immigrant populations. Based on these analyses, I argue that immigrants’ successful integration into a host country is not about the mastery of the technical skills in the dominant language. Rather, it is largely about the recognition and acceptance of the value of their language use and literacy practice as they attempt to partake in the globalized new economy.

Abstract:

This article engages in discussion on the concepts of recognition and redistribution in contemporary politic theory. It discusses the debate on the problem of identity-based injustice and the problem of economic injustice and charts the surprisingly diverse range of uses of the term recognition in recent political thought. It evaluates whether recognition is a discrete good or a general medium of social life and discusses the object of recognition and its relation to the idea of justice. It also analyses American critical theorist Nancy Fraser's views about the conflicts that arise between the politics of recognition and the politics of redistribution.

Abstract:

The final chapter concludes with five contemporary ‘uses’ of social investment, in full recognition of limits underscored by critics. The first ‘use’ of social investment therefore concerns its ‘paradigmatic’ bearings. To what extent does social investment represent a distinct policy paradigm for twenty-first-century welfare capitalism? A second ‘use’ relates to paradigm change, in the sense of theoretical progress inspiring interdisciplinary methodological innovation, in particular with respect to the empirical assessment of well-being ‘returns’ on social investment. The third more practical ‘use’ covers the identification of virtuous social investment policy mixes of ‘stocks’, ‘flows’, and ‘buffers’. The fourth ‘use’ is geographically confined to the European conundrum of overcoming the fiscal austerity to make way for social investment reform, as means to reignite socioeconomic convergence, at least for the Eurozone. The more general final use of social investment bears on the ‘politics of social investment’ in the aftermath of the financial crisis.

Abstract:

TheOxford Handbook of Psychiatric Ethicsis the most comprehensive treatment of the field in history. The editors briefly describe the goals, scope, and organization of the book. Major themes and the state of the field in the twenty-first century are then addressed. Psychiatric ethics is an excellent framework to examine social changes in psychiatry over the past 25 years. These include multiculturalism and its associated diversity of values; the transition to the digital era with new demands on confidentiality, clinical boundaries, and privacy; the empowerment of psychiatric service users as full participants and co-producers of care; the development of new technologies of assessment and treatment, varying in their invasiveness and risk; the recognition of expanded social roles for psychiatrists, and the associated virtues of psychiatric citizenship; and the development of new practice models, settings, participants, and oversight—representing profound challenges and opportunities for the ethical practice of psychiatry.

Abstract:

This book describes the new Poverty-Aware Paradigm (PAP), which was developed in Israel through intense involvement with the field of social work in various initiatives. The paradigm was adopted in 2014 by the Israeli Ministry of Welfare and Social Services as a leading paradigm for social workers in social services departments. The book draws from the rich experience of the implementation of the PAP in practice and connects examples of practice to theoretical ideas from radical/critical social work, critical poverty knowledge, and psychoanalysis. The PAP addresses poverty as a violation of human rights and emphasizes people’s ongoing efforts to resist poverty. In order to recognize these sometimes minor acts of resistance and advance their impact, social workers should establish close relationship with service users and stand by them. The book proposes combining relationship-based practice and rights-based practice as a means of bridging the gap between the emotional and material needs of service users. In addition to introducing the main concepts of the PAP, the book also contributes to the debate between conservative and cultural theories of poverty and structural theories, emphasizing the impact of a critical framework on this debate. The book consists of four parts. The first, “Transformation”, addresses the transformational nature of the paradigm. The second, “Recognition”, is based on current psychoanalytic developments and “translates” them into social work practice in order to deepen our understanding of relationship-based practice. The third, “Rights”, describes rights-based practice. The fourth, “Solidarity”, presents various ways in which solidarity might shape social workers’ practice. The book seeks to reaffirm social work’s core commitment to combating poverty and furthering social justice and to offer a solid theoretical conceptualization that is also eminently practical.

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AbstractInstagram has been an emerging platform for tourists to share their experiences and connect with other users in the multiphasic travel stages. Despite the huge number of photographs shared on Instagram on a daily basis, it remains ambiguous regarding the underlying motives of tourists’ posting behaviour. Thus, this study aims to conceptualise a framework based on the internal and external triggers of sharing travel photographs through a mix methods design involving diary studies and questionnaires. By conducting a path analysis, this study presents and validates a theoretical model including various motivational factors; namely enjoyment, self-esteem, recognition, interests, social norms, goals, social ties, social status and prestige, self-efficiency, outcome expectations and memorabilia. Meanwhile, this research clusters young techsavvy tourists into four distinct segments based on their behaviour of using Instagram while traveling. By bridging motivational theories, social psychology, and social media in the context of tourism, this research extends literature related to user-generated content and Instagram. Practically, this research allows marketers to optimise the effectiveness of marketing strategies based on the characteristics of tourists and their behaviour on social media platforms.

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Socially assistive robots can provide cognitive assistance with activities of daily living, and promote social interactions to those suffering from cognitive impairments and/or social disorders. They can be used as aids for a number of different populations including those living with dementia or autism spectrum disorder, and for stroke patients during post-stroke rehabilitation [1]. Our research focuses on developing socially assistive intelligent robots capable of partaking in natural human-robot interactions (HRI). In particular, we have been working on the emotional aspects of the interactions to provide engaging settings, which in turn lead to better acceptance by the intended users. Herein, we present a novel multimodal affect recognition system for the robot Luke, Fig. 1(a), to engage in emotional assistive interactions. Current multimodal affect recognition systems mainly focus on inputs from facial expressions and vocal intonation [2], [3]. Body language has also been used to determine human affect during social interactions, but has yet to be explored in the development of multimodal recognition systems. Body language has been strongly correlated to vocal intonation [4]. The combined modalities provide emotional information due to the temporal development underlying the neural interaction in audiovisual perception [5]. In this paper, we present a novel multimodal recognition system that uniquely combines inputs from both body language and vocal intonation in order to autonomously determine user affect during assistive HRI.

Abstract:

We present the IBM Research Scenario Planning Advisor (SPA), a decision support system that allows users to generate diverse alternate scenarios of the future and enhance their ability to imagine the different possible outcomes, including unlikely but potentially impactful futures. The system includes tooling for experts to intuitively encode their domain knowledge, and uses AI Planning to reason about this knowledge and the current state of the world, including news and social media, when generating scenarios.

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In this work, we propose an approach for recognition of compromised Twitter accounts based on Authorship Verification. Our solution can detect accounts that became compromised by analysing their user writing styles. This way, when an account content does not match its user writing style, we affirm that the account has been compromised, similar to Authorship Verification. Our approach follows the profile-based paradigm and uses N-grams as its kernel. Then, a threshold is found to represent the boundary of an account writing style. Experiments were performed using a subsampled dataset from Twitter. Experimental results showed that the developed model is very suitable for compromised recognition of Online Social Networks accounts due to the capability of recognize user styles over 95% accuracy.

Abstract:

В работе рассмотрены технологии голосового управления программным обеспечением. Описана классическая функциональная схема системы распознавания речи. Представлен анализ доступных свободно распространяемых инструментов разработчика, предназначенных для реализации голосового управления на смартфоне. The paper considers voice-user interface technologies. The traditional functional scheme of voice recognition is described. An analysis of available open source voice recognition developer tools for mobile is provided.

Abstract:

This report maps the African landscape of Open Science – with a focus on Open Data as a sub-set of Open Science. Data to inform the landscape study were collected through a variety of methods, including surveys, desk research, engagement with a community of practice, networking with stakeholders, participation in conferences, case study presentations, and workshops hosted. Although the majority of African countries (35 of 54) demonstrates commitment to science through its investment in research and development (R&D), academies of science, ministries of science and technology, policies, recognition of research, and participation in the Science Granting Councils Initiative (SGCI), the following countries demonstrate the highest commitment and political willingness to invest in science: Botswana, Ethiopia, Kenya, Senegal, South Africa, Tanzania, and Uganda. In addition to existing policies in Science, Technology and Innovation (STI), the following countries have made progress towards Open Data policies: Botswana, Kenya, Madagascar, Mauritius, South Africa and Uganda. Only two African countries (Kenya and South Africa) at this stage contribute 0.8% of its GDP (Gross Domestic Product) to R&D (Research and Development), which is the closest to the AU’s (African Union’s) suggested 1%. Countries such as Lesotho and Madagascar ranked as 0%, while the R&D expenditure for 24 African countries is unknown. In addition to this, science globally has become fully dependent on stable ICT (Information and Communication Technologies) infrastructure, which includes connectivity/bandwidth, high performance computing facilities and data services. This is especially applicable since countries globally are finding themselves in the midst of the 4th Industrial Revolution (4IR), which is not only “about” data, but which “is” data. According to an article1 by Alan Marcus (2015) (Senior Director, Head of Information Technology and Telecommunications Industries, World Economic Forum), “At its core, data represents a post-industrial opportunity. Its uses have unprecedented complexity, velocity and global reach. As digital communications become ubiquitous, data will rule in a world where nearly everyone and everything is connected in real time. That will require a highly reliable, secure and available infrastructure at its core, and innovation at the edge.” Every industry is affected as part of this revolution – also science. An important component of the digital transformation is “trust” – people must be able to trust that governments and all other industries (including the science sector), adequately handle and protect their data. This requires accountability on a global level, and digital industries must embrace the change and go for a higher standard of protection. “This will reassure consumers and citizens, benefitting the whole digital economy”, says Marcus. A stable and secure information and communication technologies (ICT) infrastructure – currently provided by the National Research and Education Networks (NRENs) – is key to advance collaboration in science. The AfricaConnect2 project (AfricaConnect (2012–2014) and AfricaConnect2 (2016–2018)) through establishing connectivity between National Research and Education Networks (NRENs), is planning to roll out AfricaConnect3 by the end of 2019. The concern however is that selected African governments (with the exception of a few countries such as South Africa, Mozambique, Ethiopia and others) have low awareness of the impact the Internet has today on all societal levels, how much ICT (and the 4th Industrial Revolution) have affected research, and the added value an NREN can bring to higher education and research in addressing the respective needs, which is far more complex than simply providing connectivity. Apart from more commitment and investment in R&D, African governments – to become and remain part of the 4th Industrial Revolution – have no option other than to acknowledge and commit to the role NRENs play in advancing science towards addressing the SDG (Sustainable Development Goals). For successful collaboration and direction, it is fundamental that policies within one country are aligned with one another. Alignment on continental level is crucial for the future Pan-African African Open Science Platform to be successful. Both the HIPSSA ((Harmonization of ICT Policies in Sub-Saharan Africa)3 project and WATRA (the West Africa Telecommunications Regulators Assembly)4, have made progress towards the regulation of the telecom sector, and in particular of bottlenecks which curb the development of competition among ISPs. A study under HIPSSA identified potential bottlenecks in access at an affordable price to the international capacity of submarine cables and suggested means and tools used by regulators to remedy them. Work on the recommended measures and making them operational continues in collaboration with WATRA. In addition to sufficient bandwidth and connectivity, high-performance computing facilities and services in support of data sharing are also required. The South African National Integrated Cyberinfrastructure System5 (NICIS) has made great progress in planning and setting up a cyberinfrastructure ecosystem in support of collaborative science and data sharing. The regional Southern African Development Community6 (SADC) Cyber-infrastructure Framework provides a valuable roadmap towards high-speed Internet, developing human capacity and skills in ICT technologies, high- performance computing and more. The following countries have been identified as having high-performance computing facilities, some as a result of the Square Kilometre Array7 (SKA) partnership: Botswana, Ghana, Kenya, Madagascar, Mozambique, Mauritius, Namibia, South Africa, Tunisia, and Zambia. More and more NRENs – especially the Level 6 NRENs 8 (Algeria, Egypt, Kenya, South Africa, and recently Zambia) – are exploring offering additional services; also in support of data sharing and transfer. The following NRENs already allow for running data-intensive applications and sharing of high-end computing assets, bio-modelling and computation on high-performance/ supercomputers: KENET (Kenya), TENET (South Africa), RENU (Uganda), ZAMREN (Zambia), EUN (Egypt) and ARN (Algeria). Fifteen higher education training institutions from eight African countries (Botswana, Benin, Kenya, Nigeria, Rwanda, South Africa, Sudan, and Tanzania) have been identified as offering formal courses on data science. In addition to formal degrees, a number of international short courses have been developed and free international online courses are also available as an option to build capacity and integrate as part of curricula. The small number of higher education or research intensive institutions offering data science is however insufficient, and there is a desperate need for more training in data science. The CODATA-RDA Schools of Research Data Science aim at addressing the continental need for foundational data skills across all disciplines, along with training conducted by The Carpentries 9 programme (specifically Data Carpentry 10 ). Thus far, CODATA-RDA schools in collaboration with AOSP, integrating content from Data Carpentry, were presented in Rwanda (in 2018), and during17-29 June 2019, in Ethiopia. Awareness regarding Open Science (including Open Data) is evident through the 12 Open Science-related Open Access/Open Data/Open Science declarations and agreements endorsed or signed by African governments; 200 Open Access journals from Africa registered on the Directory of Open Access Journals (DOAJ); 174 Open Access institutional research repositories registered on openDOAR (Directory of Open Access Repositories); 33 Open Access/Open Science policies registered on ROARMAP (Registry of Open Access Repository Mandates and Policies); 24 data repositories registered with the Registry of Data Repositories (re3data.org) (although the pilot project identified 66 research data repositories); and one data repository assigned the CoreTrustSeal. Although this is a start, far more needs to be done to align African data curation and research practices with global standards. Funding to conduct research remains a challenge. African researchers mostly fund their own research, and there are little incentives for them to make their research and accompanying data sets openly accessible. Funding and peer recognition, along with an enabling research environment conducive for research, are regarded as major incentives. The landscape report concludes with a number of concerns towards sharing research data openly, as well as challenges in terms of Open Data policy, ICT infrastructure supportive of data sharing, capacity building, lack of skills, and the need for incentives. Although great progress has been made in terms of Open Science and Open Data practices, more awareness needs to be created and further advocacy efforts are required for buy-in from African governments. A federated African Open Science Platform (AOSP) will not only encourage more collaboration among researchers in addressing the SDGs, but it will also benefit the many stakeholders identified as part of the pilot phase. The time is now, for governments in Africa, to acknowledge the important role of science in general, but specifically Open Science and Open Data, through developing and aligning the relevant policies, investing in an ICT infrastructure conducive for data sharing through committing funding to making NRENs financially sustainable, incentivising open research practices by scientists, and creating opportunities for more scientists and stakeholders across all disciplines to be trained in data management.