COMUNICAÇÃO INSTITUCIONAL E UNIVERSIDADE: diretrizes para a divulgação científica no estado de Mato Grosso

O estudo visa identificar as iniciativas de Divulgação Científica empreendidas pela Universidade Federal de Mato Grosso (UFMT) e Universidade do Estado de Mato Grosso (Unemat), com vistas à atualização e ao aperfeiçoamento da comunicação institucional, maior interação com interlocutores e fortalecimento da imagem do estado como produtor de CT&I. Foram empreendidas pesquisas bibliográficas e documentais, áreas prioritárias de fomento e difusão científica; entrevistas; auditoria de imagem na mídia estadual; diagnóstico dos principais produtos de jornalismo científico desenvolvidos pela UFMT e Unemat, assim como iniciativas conjuntas (revista Fapemat Ciência e Rede de Divulgação Científica). O método investigativo adotado pode ser caracterizado como Pesquisa Participante, concebido em estreita associação com resolução de problemas, tomada de consciência ou produção de novos conhecimentos (THIOLLENT, 1996, 1997). Tal estratégia agrega distintas técnicas de pesquisa social, definidas em função de cada fase do processo de investigação. A partir da análise dos conteúdos científicos publicados nos jornais estaduais, foi possível verificar que essas IES públicas ainda não ocupam lugar relevante em tais veículos, o que pode ser justificado pela inadequação de linguagem ou canais de relacionamento, assim como, pela necessidade de uma política de divulgação mais eficiente. O mapeamento dos portais e canais de mídias sociais institucionais evidenciou que a utilização desses veículos ainda pode ser mais bem dinamizada. Por fim, as conclusões apontam que diferenças culturais e institucionais entre as duas IES inviabilizam a adoção de uma Política de Comunicação Científica integrada, comum entre UFMT e Unemat. O que pode ser considerado, é o desenvolvimento de ações para a dinamização de divulgação dessas instituições, no âmbito do Sistema Estadual de CT&I.

TrendMiner: Large-scale Cross-lingual Trend Mining Summarization of Real-time Media Streams

El reciente crecimiento masivo de medios on-line y el incremento de los contenidos generados por los usuarios (por ejemplo, weblogs, Twitter, Facebook) plantea retos en el acceso e interpretación de datos multilingües de manera eficiente, rápida y asequible. El objetivo del proyecto TredMiner es desarrollar métodos innovadores, portables, de código abierto y que funcionen en tiempo real para generación de resúmenes y minería cross-lingüe de medios sociales a gran escala. Los resultados se están validando en tres casos de uso: soporte a la decisión en el dominio financiero (con analistas, empresarios, reguladores y economistas), monitorización y análisis político (con periodistas, economistas y políticos) y monitorización de medios sociales sobre salud con el fin de detectar información sobre efectos adversos a medicamentos.

Socialising Around Media (SAM): Dynamic Social and Media Content Syndication for Second Screen

Today's generation of Internet devices has changed how users are interacting with media, from passive and unidirectional users to proactive and interactive. Users can use these devices to comment or rate a TV show and search for related information regarding characters, facts or personalities. This phenomenon is known as second screen. This paper describes SAM, an EU-funded research project that focuses on developing an advanced digital media delivery platform based on second screen interaction and content syndication within a social media context, providing open and standardised ways of characterising, discovering and syndicating digital assets. This work provides an overview of the project and its main objectives, focusing on the NLP challenges to be faced and the technologies developed so far.

La gastronomía como Industria Creativa en un contexto digital. Análisis de webs y redes sociales de los restaurantes españoles con estrella Michelin

En los últimos años es evidente el éxito creciente de la gastronomía, no sólo como mercado económico sino también desde una perspectiva comunicativa. Entendida como una Industria Creativa, la gastronomía está adquiriendo cada vez más peso en el mercado de la comunicación y se están desarrollando planes estratégicos que acercan progresivamente el sector gastronómico a todos los públicos, democratizando el arte de la cocina y haciendo de éste un talento accesible y disponible para todos los públicos. En pleno contexto de crecimiento, las estrategias y recursos comunicativos que utilizan tanto los mass media como los propios restaurantes y profesionales de la cocina, se han de convertir en objeto de estudio necesario para entender, por ejemplo, de qué manera se explotan los recursos comunicacionales y cuál es el alcance de los mismos así como sus oportunidades. El presente artículo se centra en un análisis de contenido de las páginas webs y las redes sociales utilizadas por los ocho restaurantes españoles galardonados con tres estrellas por la Guía Michelin España-Portugal (2014), sometidos a estudio en la misma semana (del 15 al 21 de septiembre). El objetivo principal es tratar de conocer estrategia de comunicación online llevada a cabo por estos restaurantes y establecer la importancia que se les atribuye a los recursos web a la hora de contribuir tanto a la consolidación de sus propias marcas como a la propia Industria Creativa gastronómica. Los resultados muestran cierta disparidad en el uso tanto de los recursos web como de los social media y avanzan que el sector gastronómico y de la restauración española tiene un reto: seguir comunicando implicándose en mayor medida con la bidireccionalidad e invitación a la participación de sus públicos, con el objetivo de captar nuevos contactos, fidelizar a los clientes actuales y convertir a todos ellos en prescriptores de sus servicios.

Dynamic Social and Media Content Syndication for Second Screen

Social networking apps, sites and technologies offer a wide range of opportunities for businesses and developers to exploit the vast amount of information and user-generated content produced through social networking. In addition, the notion of second screen TV usage appears more influential than ever, with viewers continuously seeking further information and deeper engagement while watching their favourite movies or TV shows. In this work, the authors present SAM, an innovative platform that combines social media, content syndication and targets second screen usage to enhance media content provisioning, renovate the interaction with end-users and enrich their experience. SAM incorporates modern technologies and novel features in the areas of content management, dynamic social media, social mining, semantic annotation and multi-device representation to facilitate an advanced business environment for broadcasters, content and metadata providers, and editors to better exploit their assets and increase their revenues.

O mercado da arte moderna e contemporânea em Portugal : 2005-2013

Tese de doutoramento, História (História de Arte), Universidade de Lisboa, Faculdade de Letras, 2016

A simple Bayesian modelling approach to event extraction from Twitter

With the proliferation of social media sites, social streams have proven to contain the most up-to-date information on current events. Therefore, it is crucial to extract events from the social streams such as tweets. However, it is not straightforward to adapt the existing event extraction systems since texts in social media are fragmented and noisy. In this paper we propose a simple and yet effective Bayesian model, called Latent Event Model (LEM), to extract structured representation of events from social media. LEM is fully unsupervised and does not require annotated data for training. We evaluate LEM on a Twitter corpus. Experimental results show that the proposed model achieves 83% in F-measure, and outperforms the state-of-the-art baseline by over 7%.© 2014 Association for Computational Linguistics.

Automatic labelling of topic models learned from Twitter by summarisation

Latent topics derived by topic models such as Latent Dirichlet Allocation (LDA) are the result of hidden thematic structures which provide further insights into the data. The automatic labelling of such topics derived from social media poses however new challenges since topics may characterise novel events happening in the real world. Existing automatic topic labelling approaches which depend on external knowledge sources become less applicable here since relevant articles/concepts of the extracted topics may not exist in external sources. In this paper we propose to address the problem of automatic labelling of latent topics learned from Twitter as a summarisation problem. We introduce a framework which apply summarisation algorithms to generate topic labels. These algorithms are independent of external sources and only rely on the identification of dominant terms in documents related to the latent topic. We compare the efficiency of existing state of the art summarisation algorithms. Our results suggest that summarisation algorithms generate better topic labels which capture event-related context compared to the top-n terms returned by LDA. © 2014 Association for Computational Linguistics.

On the k-anonymization of time-varying and multi-layer social graphs

The popularity of online social media platforms provides an unprecedented opportunity to study real-world complex networks of interactions. However, releasing this data to researchers and the public comes at the cost of potentially exposing private and sensitive user information. It has been shown that a naive anonymization of a network by removing the identity of the nodes is not sufficient to preserve users’ privacy. In order to deal with malicious attacks, k -anonymity solutions have been proposed to partially obfuscate topological information that can be used to infer nodes’ identity. In this paper, we study the problem of ensuring k anonymity in time-varying graphs, i.e., graphs with a structure that changes over time, and multi-layer graphs, i.e., graphs with multiple types of links. More specifically, we examine the case in which the attacker has access to the degree of the nodes. The goal is to generate a new graph where, given the degree of a node in each (temporal) layer of the graph, such a node remains indistinguishable from other k-1 nodes in the graph. In order to achieve this, we find the optimal partitioning of the graph nodes such that the cost of anonymizing the degree information within each group is minimum. We show that this reduces to a special case of a Generalized Assignment Problem, and we propose a simple yet effective algorithm to solve it. Finally, we introduce an iterated linear programming approach to enforce the realizability of the anonymized degree sequences. The efficacy of the method is assessed through an extensive set of experiments on synthetic and real-world graphs.

Mainstream media behavior analysis on Twitter:a case study on UK general election

With the development of social media tools such as Facebook and Twitter, mainstream media organizations including newspapers and TV media have played an active role in engaging with their audience and strengthening their influence on the recently emerged platforms. In this paper, we analyze the behavior of mainstream media on Twitter and study how they exert their influence to shape public opinion during the UK's 2010 General Election. We first propose an empirical measure to quantify mainstream media bias based on sentiment analysis and show that it correlates better with the actual political bias in the UK media than the pure quantitative measures based on media coverage of various political parties. We then compare the information diffusion patterns from different categories of sources. We found that while mainstream media is good at seeding prominent information cascades, its role in shaping public opinion is being challenged by journalists since tweets from them are more likely to be retweeted and they spread faster and have longer lifespan compared to tweets from mainstream media. Moreover, the political bias of the journalists is a good indicator of the actual election results. Copyright 2013 ACM.

Assessing Organizational Image: Triangulation Across Different Applicant Perceptions, Website, and Facebook Features

This study examined the role of corporate websites and company Facebook profiles in shaping perceptions of organizational image in the recruitment context. A primary purpose of this research was to determine whether or not perceptions of organizational image vary across different web-based recruitment methods, specifically examining corporate websites and social networking (SNW) sites, such as company Facebook profiles. A secondary goal was to determine how these perceptions of image are shaped by the objective components of websites and Facebook profiles. Finally, this study sought to determine the most influential components of websites and Facebook profiles, in terms of impacting image, to better understand how organizations can maximize their web-based recruitment efforts. A total of 102 companies selected from Fortune Magazine’s 2011 top 500 were chosen for the study. Perceptions of organizational personality as well as objective assessments of personality were gathered for each organization in a two phase approach. Results indicate that exposure to corporate websites and company Facebook profiles do influence perceptions of image in different ways. Furthermore, individual components of the websites were identified as key drivers for influencing specific image dimensions, particularly for company Facebook pages. Findings are beneficial for advising practitioners on how to best manage their web-based recruitment sources in order to maximize efficiency. The present study serves to further our understanding of the process through which perceptions of organizational image are influenced by new recruitment sources.

Organic Surveillance: Security and Myth in the Rural

This project looks at the ways Northeastern Ontario citizens in rural communities regulate their private property through traditional and contemporary surveillance means. Through art and objects, this project allows viewers the opportunity to experience surveillance in rural areas through visual and creative ways that encourage interaction and critique. This project defines organic surveillance by looking at the ways ruralists in Markstay Ontario practice surveillance and deterrence which is influenced by characteristics of land, risks and other determining factors such as psychology, resourcefulness, sustainability, technology and private property. Organic surveillance argues that surveillance and deterrence is prevalent far beyond datamining, GPS tracking and social media. Surveillance and deterrence as methods of survival are found everywhere, even in the farthest, most “wild” and forested areas.

CODEX: mapping co-created data for speculative geographies

This paper discusses a series of artworks named CODEX produced by the authors as part of a collaborative research project between the Centre for Research in Education, Art and Media (CREAM), University of Westminster, and the Oxford Internet Institute. Taking the form of experimental maps, large-scale installations and prints, we show how big data can be employed to reflect upon social phenomena through the formulation of critical, aesthetic and speculative geographies.

News agencies, their constant reinvention as a strategy to face competition

News agencies compete for a foothold as providers of information and mass media. Covered by a technological class infrastructure, Associated Press, Reuters, Agence FrancePresse (AFP) and EFE are leaders of the global media system because they introduce revolutionary changes in their production routines, professional culture, journalistic genres and styles; also for its innovative product offerings and services. This article also focuses on the strategies of the agencies to get closer to their audiences, from the agreements established and the treatment of very specific themes. Some solutions that contribute to the future survival of these entities are also proposed.

Media web sites interactivity: Searching new ways to dialog with their users

Currently the media have made many new tools on their websites in order to broaden the dialogue with its users, a feature that has been called interactivity. The objective of this research is to describe the interactive resources of Chilean media websites. The analysis was conducted at 20 sites using a pattern of six dimensions with interactive forms which are today using identified. The findings indicate that digital media Chileans are expanding the possibilities of dialogue with users on social media, especially Twitter and Facebook, and the mediauser interaction is monological, that is to say, from the media to the user, but with very low feedback.