A Visual Analytics System for Making Sense of Real-Time Twitter Streams

Through social media platforms, massive amounts of data are being produced. Twitter, as one such platform, enables users to post “tweets” on an unprecedented scale. Once analyzed by machine learning (ML) techniques and in aggregate, Twitter data can be an invaluable resource for gaining insight. However, when applied to real-time data streams, due to covariate shifts in the data (i.e., changes in the distributions of the inputs of ML algorithms), existing ML approaches result in different types of biases and provide uncertain outputs. This thesis describes a visual analytics system (i.e., a tool that combines data visualization, human-data interaction, and ML) to help users make sense of the real-time streams on Twitter. As proofs of concept, public-health and political discussions were analyzed. The system not only provides categorized and aggregate results but also enables the stakeholders to diagnose and to heuristically suggest fixes for the errors in the outcome

DEFLUÊNCIA MIDIÁTICA NA PERCEPÇÃO DA VERACIDADE DAS INFORMAÇÕES

Since the end of the 1970s, when the process and invention of digital social networks began until the present day, there has been a constant and growing adherence to these networks, which currently have more than three billion users. Due to the uninterrupted flow of information and consequent dynamism present in social networks, most of its users do not use them only as a form of socialization, but also as a form of data consultation (from the most diverse areas of knowledge) and as an open space for the expression of their beliefs and ideas. However, despite the qualities in relation to greater access to knowledge (given the number of users of social networks and the informality present in these) and the freedom of expression made possible by the networks, there is a very large stage for the dissemination of false news and posts, which implies the question of the growth of the disinformation cycle and the process of sharing fake news. This article carried out a systematic survey, through the base of articles and journals web of science and, subsequently, an analysis of relevant articles (impact factor and citation) seeking to understand the concept of media influence and the factors that lead people to accept certain untruths even when presented with the correct facts.Desde finales de la década de 1970, cuando comenzó el proceso y la invención de las redes sociales digitales hasta nuestros días, ha habido una adhesión constante y creciente de estas redes, que actualmente acumulan más de tres mil millones de usuarios. Debido al flujo ininterrumpido de información y el consecuente dinamismo presente en las redes sociales, la mayoría de sus usuarios no solo las utilizan como una forma de socialización, sino también como una forma de consulta de datos (desde las más diversas áreas del conocimiento) y como un espacio abierto para la expresión de sus creencias e ideas. Sin embargo, a pesar de las cualidades en relación a un mayor acceso al conocimiento (dada la cantidad de usuarios de las redes sociales y la informalidad presente en estas) y la libertad de expresión que posibilitan las redes, existe un escenario muy grande para la difusión de noticias y publicaciones falsas, lo que implica el tema del crecimiento del ciclo de desinformación y en el proceso de compartir noticias falsas. Este artículo realizó una encuesta sistemática, a través de la base de datos de artículos y revistas web of science y, posteriormente, un análisis de los artículos relevantes (factor de impacto y citación) buscando comprender el concepto de defluencia mediática y los factores que llevan a las personas a aceptar ciertas falsedades incluso cuando se presentan a los hechos correctos.Desde o fim da década de 70, quando foi iniciado o processo e a invenção das redes sociais digitais, até os dias atuais, houve uma aderência constante e crescente dessas redes, que atualmente acumulam mais de três bilhões de usuários. Pelo ininterrupto fluxo de informações e consequente dinamismo presente nas redes sociais, grande parte de seus usuários não as usam apenas como forma de socialização, mas também como forma de consulta de dados (das mais diversas áreas do conhecimento) e como um espaço aberto para a expressão de suas crenças e ideias. Porém, apesar das qualidades em relação ao maior acesso ao conhecimento (dada a quantia de usuários de redes sociais e a informalidade presente nestas) e da liberdade de expressão possibilitados pelas redes, há um palco muito grande para a difusão de notícias e postagens falsas, o que implica na questão do crescimento do ciclo de desinformação e no processo de compartilhamento de notícias de cunho falso. Este artigo fez um levantamento sistemático, por meio da base de artigos e periódicos web of science e, posteriormente, uma análise dos artigos relevantes (fator de impacto e citação) procurando entender o conceito de defluência midiática e os fatores que levam as pessoas a aceitarem certas inverdades, mesmo quando são apresentadas aos fatos corretos.Desde o fim da década de 70, quando foi iniciado o processo e a invenção das redes sociais digitais, até os dias atuais, houve uma aderência constante e crescente dessas redes, que atualmente acumulam mais de três bilhões de usuários. Pelo ininterrupto fluxo de informações e consequente dinamismo presente nas redes sociais, grande parte de seus usuários não as usam apenas como forma de socialização, mas também como forma de consulta de dados (das mais diversas áreas do conhecimento) e como um espaço aberto para a expressão de suas crenças e ideias. Porém, apesar das qualidades em relação ao maior acesso ao conhecimento (dada a quantia de usuários de redes sociais e a informalidade presente nestas) e da liberdade de expressão possibilitados pelas redes, há um palco muito grande para a difusão de notícias e postagens falsas, o que implica na questão do crescimento do ciclo de desinformação e no processo de compartilhamento de notícias de cunho falso. Este artigo fez um levantamento sistemático, por meio da base de artigos e periódicos web of science e, posteriormente, uma análise dos artigos relevantes (fator de impacto e citação) procurando entender o conceito de defluência midiática e os fatores que levam as pessoas a aceitarem certas inverdades, mesmo quando são apresentadas aos fatos corretos

Positive Branded Rumors and Preannouncements: The Potential Backfire of Consumer Response to Exciting Misinformation

Branded rumors are not new in the realm of advertising scholarship; however, many past studies have been conducted with the assumption that rumors are inherently detrimental to their related brand. The present study aimed to break this assumption by examining and legitimizing the concept of positive branded rumors. These rumors give consumers information about a new product prior to its official announcement and thus consumers are likely to develop their attitudes toward the product prematurely. Given that positive branded rumors are primarily spread through electronic word of mouth (eWOM) on social media platforms, this study examined the effects on these rumors in light of eWOM scholarship. In addition, consumers’ responses toward positive branded rumors are expected to be influenced by a brand’s eventual preannouncement that either confirms or disconfirms the rumors. Finally, studies of eWOM have indicated consumer response to eWOM is influenced by initial awareness of the related product or product line. Therefore, the dynamics among consumer rumor eWOM valence, brand preannouncement type, and consumer initial awareness were examined. A 2 (eWOM valence: positive vs. negative) x 2 (preannouncement type: confirmation vs. disconfirmation) between-subject experimental design was employed. Both eWOM valence and preannouncement type were manipulated, whereas initial awareness was measured. By using simulated Twitter posts discussing a positive branded rumor and an official preannouncement, a total of four conditions were created: 1) positive eWOM valence – confirming preannouncement, 2) positive eWOM valence – disconfirming preannouncement, 3) negative eWOM valence – confirming preannouncement, and 4) negative eWOM valence – disconfirming preannouncement. Through an online experiment, participants were randomly exposed to one of the four conditions. Questions regarding participants’ attitudes toward the subject product and brand, emotional reactions toward the preannouncement, and purchase intent of the product in the preannouncement were asked. The results of this experiment revealed rumor eWOM valence to be influential on its own in developing brand attitudes. Positive eWOM led to more positive brand attitudes, compared to negative eWOM. Additionally, eWOM valence and preannouncement type were found to interact in the development of product and brand attitudes. The results showed negative eWOM to dampen participants’ attitudes even when the rumored product was confirmed. Additionally, the experiment revealed a backfire from disconfirming a rumor when participants had previously been exposed to positive eWOM about that rumor. No significant results were found for any three-way interaction between eWOM valence, preannouncement type, and initial awareness. These results hold implications for future scholarship of branded rumors, particularly in further legitimizing the concept of positive branded rumors as well as the unique effects of those rumors. Additionally, these results reveal a need to further explore theoretical lenses through which to view this phenomenon as the effects of rumor eWOM found here do not fully match the predictions of other studies of general eWOM. Finally, this study poses implications for brand practitioners by revealing a need to know and understand online rumor discourse around their brand to develop effective and appropriate rumor response strategies

Microblog Analysis as a Program of Work

Inspired by a European project, PHEME, that requires the close analysis of Twitter-based conversations in order to look at the spread of rumors via social media, this article has two objectives. The first of these is to take the analysis of microblogs back to first principles and lay out what microblog analysis should look like as a foundational program of work. The other is to describe how this is of fundamental relevance to human-computer interaction's interest in grasping the constitution of people's interactions with technology within the social order. Our critical finding is that, despite some surface similarities, Twitter-based conversations are a wholly distinct social phenomenon requiring an independent analysis that treats them as unique phenomena in their own right, rather than as another species of conversation that can be handled within the framework of existing conversation analysis. This motivates the argument that microblog analysis be established as a foundationally independent program, examining the organizational characteristics of microblogging from the ground up. We articulate how aspects of this approach have already begun to shape our design activities within the PHEME project