Orientador: Rafael de Almeida Evangelista / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Estudos da Linguagem e Laboratório de Estudos Avançados em Jornalismo / Made available in DSpace on 2018-08-27T09:25:57Z (GMT). No. of bitstreams: 1 Rodrigues_MeghiedeSousa_M.pdf: 3485533 bytes, checksum: 84a876a79df9443267772628adec81b1 (MD5) Previous issue date: 2015 / Resumo: O intuito que motivou esta pesquisa foi, em um escopo mais alargado, perceber em que medida a divulgação científica está mudando com o uso da Internet no Brasil. Mais especificamente, perceber como os modelos de comunicação pública da ciência se confluem no espaço digital e, perceber se, com o advento das tecnologias em rede, estaria surgindo um novo modelo para além das noções de déficit, diálogo e participação em divulgação científica (TRENCH, 2008) como se conhece hoje. Os caminhos apontados pelo estudo, no entanto, fizeram com que se chegasse a outras avaliações, mais interessantes do que o que o plano inicial poderia prever. Ao invés de fazer uma correspondência entre teoria e prática, modelo e aplicação através de uma análise discursiva dos manuais de divulgação científica (para observar como materializam a ideia de "modelo de comunicação pública de ciência") e da análise de páginas na Internet para saber como déficit, diálogo e participação se manifestam na prática, foi possível revisitar e colocar alguns questionamentos sobre a própria noção de "modelo" e tomar o mapeamento de campo também como problema. A partir daí, foi possível sugerir que o conceito de modulação, de Gilles Deleuze (2000) pode ser um caminho interessante para ajudar a pensar estes modelos, bem como perceber algumas questões que inquietam uma parcela dos divulgadores de ciência no Brasil no que toca sua própria prática ¿ e algumas ideias que informam suas opiniões sobre jornalista, cientista e público. Assim, foi possível perceber, ainda que de forma inicial, que pode ser que modelo e modulação se sobreponham e funcionem sem a necessidade de que um prescinda do outro, embora sejam formulações diferentes. E pode ser que esta seja uma das formas como a divulgação científica aponta para mudanças no meio digital / Abstract: The initial aim of this research was, in a larger scope, notice to what measure science communication is changing with Internet use in Brazil. More in specific, to notice how models of public communication of science blend within the digital space and notice whether, with the emergence of network technologies, a new model besides the currently known notions of deficit, dialogue and participation (TRENCH, 2008) could be looming. The route taken at this study, though, made possible some other evaluations, more interesting than the initial plan could foresee. Instead of making a correspondence between theory and practice, model and application through a discourse analysis of science communication handbooks (so that it could be possible to observe how the idea of "models in public communication of science" materializes) and the study of webpages in order to know how deficit, dialogue and participation manifest in practice, it was possible to revisit and put forth some questions about the notion of "model" itself, and also take the mapping of the field as a problem. From there, it was possible to suggest that the concept of modulation, as in Gilles Deleuze (2000) can be an interesting way to help think these models, as well as notice some issues that disquiet a parcel of science communicators in Brazil in what regards their own practice ¿ and some ideas that inform their opinion about journalist, scientist and public. Therefore, it was possible to notice, even in a still feeble way, that it might be that model and modulation superpose and work without necessarily annulling each other, even being different formulations. And it might be that this is one among the many ways science communication is changing within the digital environment / Mestrado / Divulgação Científica e Cultural / Mestra em Divulgação Científica e Cultural

Com a popularidade e o crescimento das Redes Sociais Online, o interesse pelo entendimento de como seus usuários interagem entre si também tem crescido, configurando assim um cenário rico no qual são criadas oportunidades para melhorar o design de interfaces, compreender a organização de movimentos sociais, o marketing viral e a distribuição de conteúdos multimídia, dentre outros. Na investigação dessas oportunidades de pesquisa, um modelo de representação da atividade dos usuários amplamente empregado é baseado na construção de um grafo. Embora as atividades dos usuários em uma Rede Social Online sejam variadas, assim como as possibilidades de interação entre usuários, a construção de um grafo normalmente considera uma interação específica, que é então analisada a partir da interpretação de medidas baseadas em grafos ou de medidas estatísticas. Técnicas de mineração de dados podem ser empregadas de forma alternativa e complementar ao modelo baseado em grafos, possibilitando a extração e a avaliação de padrões das atividades de usuários. Entretanto, tanto na análise baseada em grafos quanto na utilização de técnicas de mineração de dados, a literatura reporta trabalhos em que são implicitamente representados elementos associados com a atividade dos usuários como ações executadas, mídias compartilhadas, aplicações e tipos de dispositivos utilizados. Nesse cenário, existe uma demanda por um modelo descritivo que permita a representação explícita dos elementos associados com as atividades dos usuários representação essa que possa ser utilizada na extração e na avaliação das interações entre usuários. Para atender essa demanda, nesta tese é apresentada uma técnica e um método para representar, extrair e avaliar interações entre usuários de Redes Sociais Online. São também reportados resultados de experimentos da aplicação da técnica e do método a partir de dados obtidos de uma Rede Social Online / The interest in understanding user interactions is increasing with the popularity of Online Social Networks. This scenario leads to rich opportunities to improve the design of interfaces, to understand the organization of social movements, to model the dynamics of viral marketing and to characterize the distribution of multimedia content, among others. In the investigation of these research opportunities, a widely used representation of users activities is based on graphs as underlying data models. Graph data models usually consider a specific interaction, which is analyzed based on the interpretation of statistical measures and graph-based measures. On the other hand, user activities and possibilities of interaction in social networks are multifaceted, so that singleinteraction graph-based approaches might prove to be unfeasible to properly model the problem. In order to deal with these limitations, data mining techniques may be employed as an alternative to graph-based modeling approaches, by enabling extraction and evaluation of users activities as patterns. However, both in the use of the model graph-based as in the use of data mining techniques, the literature reports an implicit representation of elements associated with the users activities such as executed actions, shared media, used applications and devices. In this scenario, there is a demand for a descriptive model which allows explicit representation of the elements associated with users activities - this representation can be used in the extraction and evaluation of interactions among users. To meet this demand, this thesis presents a technique and a method to represent, to extract and to evaluate interactions among users of Online Social Networks. Results of experimentation of applying the technique and method based on data obtained from an Online Social Network are also reported

Thesis (M.Inf) --University of Limpopo, 2019. / The use of social media (SM) tools in both public and private institutions is growing remarkably. Academic libraries, in particular are confronted with serious challenges of becoming the leader in adopting various SM platforms to enhance the delivery of library and information services to their users. This study investigated the extent and ways in which librarians attached to the University of Limpopo library use SM platforms in the provision of library and information services to their patrons. The study examined types of SM tools used, purposes that SM tools are used for in academic libraries, factors that determine and impede the use of SM, as well as the attitudes of the library staff towards the use of SM in providing library and information services. The study adopted a qualitative research approach through the use of a semi-structured interview (administered face-to-face) with 10 academic librarians at the University of Limpopo (UL) as a data collection method. The findings of the study show that UL library staff largely use SM platforms such as Facebook to market and promote library services as well as Library-Blog to liaise with the schools or faculties. The study further revealed that librarians at UL are not in charge of SM applications. Instead the Marketing and Communication Department administrator is responsible for the management of SM in the university. The study notes that library personnel are aware of various SM platforms. Therefore, it has a direct influence on their use in work-related tasks. Moreover, the ease of use, low cost, high demand and usefulness of SM applications are contributory factors which motivated the librarians to want to use it. The study further reveals factors that inhibit the effective use of these applications and recommends that library management should create SM policies to boost the effective use of SM for the benefit of library patrons.

In recent years, social media has experienced tremendous growth in the number of users. Facebook alone has more than 1.3 billion active users and Twitter has attracted over 600 million active users. Social media has significantly changed the way humans communicate. Many people use social media to keep in touch with family and friends and receive up-to-date information about what happens around the world. Politicians are using social media to support their campaigns. Use of social media is not restricted to individuals and politicians. Businesses are now using social media to promote their products and services. Many companies maintain Facebook and Twitter accounts to keep in touch with their customers. Consumers also use social media to receive information about products/services. Online product reviews are now an important source of information for consumers. This dissertation aims to address one fundamental research question: how do individual differences among users lead to different levels of performance on social media? More specifically, this dissertation investigates the motivations of use and the predictors of performance in the context of social media. We utilize sentiment mining to predict performance in different types of social media including information diffusion in Twitter and helpfulness and readership of online consumer reviews. The results show how different motivations lead to different levels of participation in social media and level of participation consequently influences performance. We also find that sentiment of the messages posted on social media significantly influence their performance.

Social media use is a pivotal driver for political engagement. The present study extended previous research by exploring the simple and serial mediating roles of narcissism, perceived anonymity, descriptive norms, and subjective norms in this relationship. Structural equation modeling (SEM) with bootstrapping estimation was conducted for hypothesis testing using data from 579 Hong Kong university students. Modeling results revealed that perceived anonymity, descriptive norms, and subjective norms are significant mediators of the relationship between social media use and political participation. Moreover, descriptive norms, together with perceived anonymity, were found to mediate the relationship. Likewise, narcissism combined with descriptive norms proved to be significant mediators of the relationship. Additionally, a distal mediation effect of descriptive norms and subjective norms proved to be significant. Based on these results, a subsequent parallel mediation analysis was conducted, revealing that perceived anonymity is the most influential indicator among perceived anonymity, subjective norms, and descriptive norms of the relationship of social media use and political participation. The study concluded by comparing male and female respondents in terms of political participation. The result showed that male respondents were generally more active than female respondents in both online and offline political activities, which agrees with prior research findings. Collectively, the current study provides a new perspective from which we can further understand the effects of social media use on political engagement.

Les réseaux sociaux numériques ont pris une place prépondérante dans l'espace informationnel, et sont souvent utilisés pour la publicité, le suivi de réputation, la propagande et même la manipulation, que ce soit par des individus, des entreprises ou des états. Alors que la quantité d'information rend difficile son exploitation par des humains, le besoin reste entier d'analyser un réseau social numérique : il faut dégager des tendances à partir des messages postés dont notamment les opinions échangées, qualifier les comportements des utilisateurs, et identifier les structures sociales émergentes.Pour résoudre ce problème, nous proposons un système d'analyse en trois niveaux. Tout d'abord, l'analyse du message vise à en déterminer l'opinion. Ensuite, la caractérisation et l'évaluation des comptes utilisateurs est réalisée grâce à une étape de profilage comportemental et à l'étude de leur importance et de leur position dans des graphes sociaux, dans lesquels nous combinons les mesures topologiques d'importance des noeuds dans un graphe avec les statistiques d'engagement, par exemple en nombre d'abonnés. Enfin, le système procède à la détection et à l'évaluation de communautés d'utilisateurs, pour lesquelles nous introduisons des scores de cohésion thématique qui complètent les mesures topologiques classiques de qualité structurelle des communautés détectées. Nous appliquons ce système d'analyse sur deux corpus provenant de deux médias sociaux différents : le premier est constitué de messages publiés sur Twitter, représentant toutes les activités réalisées par 5 000 comptes liés entre eux sur une longue période. Le second provient d'un réseau social basé sur TOR, nommé Galaxy2. Nous évaluons la pertinence de notre système sur ces deux jeux de données, montrant la complémentarité des outils de caractérisation des comptes utilisateurs (influence, comportement, rôle) et des communautés de comptes (force d'interaction, cohésion thématique), qui enrichissent l'exploitation du graphe social par les éléments issus des contenus textuels échangés. / Online Social Networks have taken a huge place in the informational space and are often used for advertising, e-reputation, propaganda, or even manipulation, either by individuals, companies or states. The amount of information makes difficult the human exploitation, while the need for social network analysis remains unsatisfied: trends must be extracted from the posted messages, the user behaviours must be characterised, and the social structure must be identified. To tackle this problem, we propose a system providing analysis tools on three levels. First, the message analysis aims to determine the opinions they bear. Then, the characterisation and evaluation of user accounts is performed thanks to the union of a behavioural profiling method, the study of node importance and position in social graphs and engagement and influence measures. Finally the step of user community detection and evaluation is accomplished. For this last challenge, we introduce thematic cohesion scores, completing the topological, graph-based measures for group quality. This system is then applied on two corpora, extracted from two different online social media. The first is constituted of messages published on Twitter, gathering every activity performed by a set of 5,000 accounts on a long period. The second stems from a ToR-based social network, named Galaxy2, and includes every public action performed on the platform during its uptime. We evaluate the relevance of our system on these two datasets, showing the complementarity of user account characterisation tools (influence, behaviour and role), and user account communities (interaction strength, thematic cohesion), enriching the social graph exploitation with textual content elements.

The Internet increases the demand for the development of commercial applications and services that can provide better shopping experiences for customers globally. It is full of information and knowledge sources that might confuse customers. This requires customers to spend additional time and effort when they are trying to find relevant information about specific topics or objects. Recommendation systems are considered to be an important method that solves this issue. Incorporating recommendation systems in online social networks led to a specific kind of recommendation system called social recommendation systems which have become popular with the global explosion in social media and online networks and they apply many prediction algorithms such as data mining techniques to address the problem of information overload and to analyze a vast amount of data. We believe that offering a real-time social recommendation system that can understand the real context of a user’s conversation dynamically is essential to defining and recommending interesting objects at the ideal time. In this thesis, we propose an architecture for a real-time social recommendation system that aims to improve word usage and understanding in social media platforms, advance the performance and accuracy of recommendations, and propose a possible solution to the user cold-start problem. Moreover, we aim to find out if the user’s social context can be used as an input source to offer personalized and improved recommendations that will help users to find valuable items immediately, without interrupting their conversation flow. The suggested architecture works as a third-party social recommendation system that could be incorporated with other existing social networking sites (e.g. Facebook and Twitter). The novelty of our approach is the dynamic understanding of the user-generated content, achieved by detecting topics from the user’s extracted dialogue and then matching them with an appropriate task as a recommendation. Topic extraction is done through a modified Latent Dirichlet Allocation topic modeling method. We also develop a social chat app as a proof of concept to validate our proposed architecture. The results of our proposed architecture offer promising gains in enhancing the real-time social recommendations.

This dissertation studies economic issues in the digital economy with a specific focus on the economic aspects of how firms acquire and use consumer data. Chapter 1 empirically studies the drivers of digital attention in the space of social media applications. In order to do so I conduct an experiment where I comprehensively monitor how participants spend their time on digital services and use parental control software to shut off access to either their Instagram or YouTube. I characterize how participants substitute their time during and after the restrictions. I provide an interpretation of the substitution during the restriction period that allows me to conclude that relevant market definitions may be broader than those currently considered by regulatory authorities, but that the substantial diversion towards non-digital activities indicates significant market power from the perspective of consumers for Instagram and YouTube. I then use the results on substitution after the restriction period to motivate a discrete choice model of time usage with inertia and, using the estimates from this model, conduct merger assessments between social media applications. I find that the inertia channel is important for justifying blocking mergers, which I use to argue that currently debated policies aimed at curbing digital addiction are important not only just in their own right but also from an antitrust perspective and, in particular, as a potential policy tool for promoting competition in these markets. More broadly, my paper highlights the utility of product unavailability experiments for demand and merger analysis of digital goods. I thank Maayan Malter for working together with me on collecting the data for this paper. Chapter 2 then studies the next step in consumer data collection process – the extent to which a firm can collect a consumer’s data depends on privacy preferences and the set of available privacy tools. This chapter studies the impact of the General Data Protection Regulation on the ability of a data-intensive intermediary to collect and use consumer data. We find that the opt-in requirement of GDPR resulted in 12.5% drop in the intermediary-observed consumers, but the remaining consumers are trackable for a longer period of time. These findings are consistent with privacy-conscious consumers substituting away from less efficient privacy protection (e.g, cookie deletion) to explicit opt out—a process that would make opt-in consumers more predictable. Consistent with this hypothesis, the average value of the remaining consumers to advertisers has increased, offsetting some of the losses from consumer opt-outs. This chapter is jointly authored with Yeon-Koo Che and Tobias Salz. Chapter 3 and Chapter 4 make up the third portion of the dissertation that studies one of the most prominent uses of consumer data in the digital economy – recommendation systems. This chapter is a combination of several papers studying the economic impact of these systems. The first paper is a joint paper with Duarte Gonçalves which studies a model of strategic interaction between producers and a monopolist platform that employs a recommendation system. We characterize the consumer welfare implications of the platform’s entry into the production market. The platform’s entry induces the platform to bias recommendations to steer consumers towards its own goods, which leads to equilibrium investment adjustments by the producers and lower consumer welfare. Further, we find that a policy separating recommendation and production is not always welfare improving. Our results highlight the ability of integrated recommender systems to foreclose competition on online platforms. The second paper turns towards understanding how such systems impact consumer choices and is joint with Duarte Gonçalves and Shan Sikdar. In this paper we study a model of user decision-making in the context of recommender systems via numerical simulation. Our model provides an explanation for the findings of Nguyen et. al (2014), where, in environments where recommender systems are typically deployed, users consume increasingly similar items over time even without recommendation. We find that recommendation alleviates these natural filter-bubble effects, but that it also leads to an increase in homogeneity across users, resulting in a trade-off between homogenizing across-user consumption and diversifying within-user consumption. Finally, we discuss how our model highlights the importance of collecting data on user beliefs and their evolution over time both to design better recommendations and to further understand their impact.

Recognizing the importance of civic engagement to the health of local communities and the overall success of a democracy, this research sought to better understand the relationship between online media use and civic engagement. Specifically, the constructive potential of the social networking site Facebook was explored using the theoretical framework of communication infrastructure theory (CIT; Ball-Rokeach, Kim, & Matei, 2001). Results of a cross-sectional survey with a national sample of 375 participants indicated that Facebook does hold potential for civic engagement. The two most important findings of the research were that Facebook facilitated connection to neighborhood storytelling and that connection to storytelling was positively associated with civic engagement. As such, results indicated that Facebook holds potential for civic engagement insofar as the site facilitates connection to neighborhood storytelling. Additionally, Facebook was a regular part of participants’ daily routines, a means to maintain social capital, and a forum for occasional civic participation. Cumulatively, these results highlight a number of strengths that citizens and communities can build upon to improve social capital and increase civic engagement.

Autistic individuals experience marginalization and stigmatization, and are often not connected to mainstream services or organizations fostering peer relationships (Boundy, 2008; Jaarsma & Welin, 2012; Robertson, 2010). Therefore, the accomplishments of the online Autistic community in building a community for self-advocacy, peer-support, friendships, and identity development (Brownlow & O'Dell, 2006; Kidney, 2012) are important to recognize, empirically examine, and promote (Blume, 1997a; Davidson, 2008). Utilizing a community-based participatory research approach (CBPR; Israel, Schulz, Parker, & Becker, 1998) the Academic Autistic Spectrum Partnership in Research and Education (AASPIRE; www.aaspire.org) conducted the AASPIRE Internet Use, Community, and Well-Being Study, and collected data from 151 autistic adults and 173 non-autistic adults. The current study utilized data from the AASPIRE Internet Use, Community, and Well-Being Study on involvement in the online Autistic community, communication preferences, Autistic identity, and self-determination. The aims and rationale for the study were to contribute to the small body of quantitative literature on the online Autistic community, including expanding on findings that support positive outcomes of involvement in the online Autistic community (Kidney, 2012), and whether communication preference influences the relationships. The study also sought to examine the fit of an integrated model of associations among involvement in the online Autistic community, Autistic Identity, and self-determination in autistic adults who do and do not prefer online communication. Additionally, the study aimed to promote positive Autistic research and the voices of autistic participants and CBPR partners by challenging common misperceptions about autistic individuals and community/social interactions, understand the impact of communication preference, and inform policy and education designed for autistic individuals. The study used data to develop a multi-dimensional construct of involvement in the online community as well as explore the Autistic Identity Scale. The main findings included positive relationships between involvement in the online Autistic community and Autistic identity (r=.33, p<.01), as well as between involvement and self-determination (r=.38, p<.01) in autistic adults. Exploratory analyses yielded mixed results in the cross-sectional sample that was relatively limited in demographic diversity and small considering the number and type of analyses (n=324). Main findings include no moderating impact of preference to communicate online or population type (autistic or non-autistic) on the significant relationships between (1) involvement in the online community and self-determination or (2) involvement in the online community and Autistic identity. However, exploring the relationships among the variables with structural equation modeling, analyses indicated that no significant relationship exists between involvement in the online Autistic community and self-determination in autistic adults who do not prefer online communication. Findings indicate the need for further research on the complex impact of communication preference in larger samples of autistic adults. Despite sample limitations and mixed results from exploratory analyses, the findings mostly support the associations of involvement in the online Autistic community with Autistic identity and self-determination. The discussion addresses implications of the findings for theory, research, and action. For example, findings may influence how autistic individuals are provided education about and access to new media for fostering community, or lead to the development of online interventions or techniques for the promotion of positive outcomes in autistic individuals.