‘Trendy’ cities: exploring the adoption of different types of social media by Portuguese municipalities

What are the determinants of social media adoption by local government? This ongoing research provides a tentative answer to this question by analysing the 308 municipalities in Portugal. Extending previous analyses of Facebook and/or Twitter usage levels, we examine why local governments adopt a particular social media platform. More concretely, we explore, with statistical analyses, the determinants of the adoption of different types of social media. We investigate the adoption of three extremely popular social media (i.e. Facebook, Twitter and YouTube) as well as possible alternatives to those, more popular, applications. Since these platforms have distinct natures and can serve diverse purposes, we examine to what extent aspects such as local government’s commitment to transparency and participation, administrative capacity, media landscape, and socio-demographic and economic factors can explain the adoption of certain social media platforms. The results show that, indeed, demographic characteristics and administrative capacity are important factors for the adoption of less popular social media. Surprisingly, we also observe a geographical difference in municipalities’ social media adoption, with the south, in this regard, being ‘trendier’, or more innovative, than the north.This paper is a result of the project “SmartEGOV: Harnessing EGOV for Smart Governance (Foundations, methods, Tools)/NORTE-01-0145-FEDER-000037”, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (EFDR). António Tavares acknowledges the financial support of the Portuguese Foundation for Science and Technology and the Portuguese Ministry of Education and Science through national funds [Grant No. UID/CPO/0758/2019]

Mídias Sociais e Administração Pública: Análise do sentimento social perante a atuação do governo federal brasileiro

Este estudo procurou identificar como a análise de sentimento, baseada em textos extraídos de mídias sociais, pode ser um instrumento de mensuração da opinião pública sobre a atuação do governo de forma a contribuir para a avaliação da administração pública. Trata-se de um estudo aplicado, interdisciplinar, exploratório, qualitativo e quantitativo. Foram revisadas as principais formulações teóricas e conceituais acerca do tema e realizadas demonstrações práticas, utilizando-se uma ferramenta de mineração de opinião que proporcionou precisão satisfatória no processamento de dados. Para fins de demonstração, foram selecionados temas que motivaram a realização da onda de protestos que envolveu milhões de pessoas no Brasil em junho de 2013. Foram coletadas, processadas e analisadas, aproximadamente, 130.000 mensagens postadas no Facebook e no Twitter sobre esses temas em dois períodos distintos. Por meio desta investigação, observou-se que a análise de sentimento pode revelar a opinião polarizada dos cidadãos quanto à atuação do governo

Social media conflicts during the financial crisis: Managerial implications for retail banks

Social media can be used proactively to disseminate accurate corporate information and address undesirable consumer behaviors online in order to help counteract negativity in the business environment in the wake of a financial crisis. Social media thus has become a popular open forum for financial institutions such as retail banks to engage in corporate dialogue with consumers. We recommend that financial services firms preemptively use their social media?based online communities in order to disseminate accurate corporate information in times of a financial crisis. Particularly, firms can choose between a range of reactive and proactive strategies to manage social conflict in the wake of a financial crisis

Longitudinal Assessment of Working Memory Performance in the APPswe/PSEN1dE9 Mouse Model of Alzheimer’s Disease Using an Automated Figure-8-Maze

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder, with a long preclinical and prodromal phase. To enable the study of disease mechanisms, AD has been modeled in many transgenic animal lines and cognitive functioning has been tested using several widely used behavioral tasks. These tasks, however, are not always suited for repeated longitudinal testing and are often associated with acute stress such as animal transfer, handling, novelty, or stress related to the task itself. This makes it challenging to relate cognitive dysfunction in animal models to cognitive decline observed in AD patients. Here, we designed an automated figure-8-maze (F8M) to test mice in a delayed alternation task (DAT) in a longitudinal manner. Mice were rewarded when they entered alternate sides of the maze on subsequent trials. Automation as well as connection of the F8M set-up with a home cage reduces experimenter interference and minimizes acute stress, thus making it suitable for longitudinal testing and facilitating clinical translation. In the present study, we monitored cognitive functioning of 2-month-old APPswe/PSEN1dE9 (APP/PS1) mice over a period of 4 months. The percentage of correct responses in the DAT did not differ between wild-type and transgenic mice from 2 to 6 months of age. However, 6-month-old mice displayed an increase in the number of consecutive incorrect responses. These results demonstrate the feasibility of longitudinal testing using an automated F8M and suggest that APP/PS1 mice are not impaired at delayed spatial alternation until 6 months of age under the current experimental conditions

What can social media data add to the knowledge of arts and humanities? an empirical investigation on twitter at teatro alla scala

Social media, considered as a representative example of big data with their high volumes, high velocity and high variety features, are continuously receiving attention in the arts and humanities literature. While studies on the potentialities of social media to enhance audience engagement, informal learning or marketing activities in arts and cultural organisations are growing, there is limited evidence on the opportunities provided by data extracted from social media to enhance knowledge management in the arts and humanities. Acknowledging this gap, this chapter aims at understanding if and how social media data can contribute to generating new knowledge in the arts and humanities with a specific investigation on Twitter at Teatro Alla Scala. The results of the analysis are twofold. First, this study proposes a methodology to approach social media, by detailing the phases for data understanding and extraction, and the methodological approach to enhance data reliability. Second, this study identifies a set of key performance indicators that can be computed starting from social media data; the proposed indicators are finalised to develop a better knowledge of the network of social media users connected with the investigated organisation

A framework to measure e-participation level of government social media accounts

© 2019 held by the owner/author(s). Publication rights licensed to Association for Computing Machinery. There is a rising attention to the importance of social media for e-participation due to its value in creating a convenient communication channel with citizens. Evaluating e-participation is eventually an important milestone for progress. The objective of this research is to provide guidelines for a framework that assesses e-participation on government\u27s social accounts. Based on the work of Tambouris at el., 2007 [1] and Nelimarkka at el., 2014 [2], the research proposes a framework that could be applied to Facebook government accounts. This research though covers three major gaps in previous e-participation assessment research: scarcity in evaluating eparticipation within developing contexts, reliance on limited rather than large-scale empirical data, focusing on online government portals as an assessment e-participation platform and not considering social accounts\u27 performance. This research is supported by Crowd Analyzer [3], a social media monitoring tool, to enable data crawling and users comments\u27 sentiment analysis