Scottish Community Councils online: the 2014 survey.

This document reports the results of a survey, carried out in late spring 2014, of the public web presences of potentially over 1300 Scottish Community Councils (CCs). It follows on from similar survey in summer 2012. The report reviews content-types associated with up-to-date presences and examines Community Councils’ social media use, using three archetypes which may be used to derive models and examples of good practice, and create recommendations for Community Councils and their Local Authorities (LAs). The research found that there has little change overall since 2012, which combined with a high level of churn implies an increasing number of digitally disengaged Community Councils. A good way forward would be for to CCs emulate and adapt the examples of good practice identified, by publishing minutes, news, planning and local area information, limiting publication of other types of content, and using social media to engage with citizens. A number of broader recommendations are made to LAs, including that that they publish CC schemes on their websites, provide training in online methods and work together via their CCLOs and IT teams to support CCs

Local studies collections online: an investigation in Irish public libraries

Barry, L., Tedd, L.A. (2008). Local studies collections online: an investigation in Irish public libraries. Program: electronic library and information systems, 42(2), 163-186.

Who has the Right to Govern Online Activity? A Criminal and Civil Point of View

Kohl, U. (2004). Who has the right to govern online activity? A criminal and civil point of view. International Review of Law, Computers & Technology 18 (3), 387-410 RAE2008

Jurisdiction and the Internet: Regulatory Competence over Online Activity

null RAE2008

Ignorance is no Defence but is Inaccessibility? On the Accessibility of National Laws to Foreign Online Publishers

Kohl, U. (2005). Ignorance is no Defence but is Inaccessibility? On the Accessibility of National Laws to Foreign Online Publishers. Information & Communities Technology Law, 14 (1), 25-41. RAE2008 Information & Communications Technology Law Volume 14, Issue 1, 2005 Special Issue: GATED COMMUNITIES

Which of the three action-oriented corporate social responsibility (CSR) types is the most effective in improving the public attitude toward tobacco companies?

Dissertação apresentada à Universidade Fernando Pessoa como parte dos requisitos para a obtenção do grau de Mestre em Ciências da Comunicação, ramo de Marketing e Publicidade

Publicidade na promoção de serviços de medicina dentária

Projeto de Pós-Graduação/Dissertação apresentado à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Medicina Dentária

An Online Distributed Algorithm for Inferring Policy Routing Configurations

We present an online distributed algorithm, the Causation Logging Algorithm (CLA), in which Autonomous Systems (ASes) in the Internet individually report route oscillations/flaps they experience to a central Internet Routing Registry (IRR). The IRR aggregates these reports and may observe what we call causation chains where each node on the chain caused a route flap at the next node along the chain. A chain may also have a causation cycle. The type of an observed causation chain/cycle allows the IRR to infer the underlying policy routing configuration (i.e., the system of economic relationships and constraints on route/path preferences). Our algorithm is based on a formal policy routing model that captures the propagation dynamics of route flaps under arbitrary changes in topology or path preferences. We derive invariant properties of causation chains/cycles for ASes which conform to economic relationships based on the popular Gao-Rexford model. The Gao-Rexford model is known to be safe in the sense that the system always converges to a stable set of paths under static conditions. Our CLA algorithm recovers the type/property of an observed causation chain of an underlying system and determines whether it conforms to the safe economic Gao-Rexford model. Causes for nonconformity can be diagnosed by comparing the properties of the causation chains with those predicted from different variants of the Gao-Rexford model.

Online and Offline Character Recognition Using Alignment to Prototypes

Nearest neighbor classifiers are simple to implement, yet they can model complex non-parametric distributions, and provide state-of-the-art recognition accuracy in OCR databases. At the same time, they may be too slow for practical character recognition, especially when they rely on similarity measures that require computationally expensive pairwise alignments between characters. This paper proposes an efficient method for computing an approximate similarity score between two characters based on their exact alignment to a small number of prototypes. The proposed method is applied to both online and offline character recognition, where similarity is based on widely used and computationally expensive alignment methods, i.e., Dynamic Time Warping and the Hungarian method respectively. In both cases significant recognition speedup is obtained at the expense of only a minor increase in recognition error.

An overview of online-research in information systems

As the Internet has changed communication, commerce, and the distribution of information, so it is changing Information Systems Research (ISR). The goal of this paper is to put the topic of application and reliability of online research into the focus of ISR by exploring the extension of online research methods (ORM) into its popular publication outlets. 513 articles from high ranked ISR publication outlets from the last decade have been analyzed using online content analysis. The findings show that in ISR online research methods are applied despite the missing discussion on the validity of the theories and methods that were defined offline within the new environment and the associated challenges.

Matching and sorting in online dating

Using data on user attributes and interactions from an online dating site, we estimate mate preferences, and use the Gale-Shapley algorithm to predict stable matches. The predicted matches are similar to the actual matches achieved by the dating site, and the actual matches are approximately efficient. Out-of-sample predictions of offline matches, i.e., marriages, exhibit assortative mating patterns similar to those observed in actual marriages. Thus, mate preferences, without resort to search frictions, can generate sorting in marriages. However, we underpredict some of the correlation patterns; search frictions may play a role in explaining the discrepancy.

Online and Traditional Lectures: Evaluating Effects of Social Presence and Learner Control

Online courses are rapidly replacing traditional, face-to-face lectures in American universities (Allen & Seaman, 2011). As technology improves, this trend will likely continue and accelerate. Researchers must evaluate the impact of online courses compared to their traditional counterparts. This two-part study quantifies the effect of two variables – social presence and learner control – on students’ recall, application and perceived learning levels in different lecture formats. Students in introductory courses at a four-year, public, American university were randomly assigned into three groups to view distinct lecture formats, one in a traditional classroom and two via the Internet. Upon viewing the single lecture, the students were asked to fill out a test and survey to quantify teacher immediacy, recall and application, and perceived learning levels across lecture formats. The study found that different levels of social presence and learner control affected students’ perceived learning levels but did not impact recall or application.

Beyond LibGuides: The Past, Present, and Future of Online Research Guides

© 2015, Jon C. Giullian and Ernest A. Zitser.The proliferation of research guides created using the LibGuides platform has triggered extensive discussion touting their benefits for everything from assessment, engagement, and marketing, to outreach and pedagogy. However, there is at present a relative paucity of critical reflection about the product’s place in the broader informational landscape. This article is an attempt to redress this lacuna. Relying primarily on examples from the field of Slavic, East European, and Eurasian studies, the authors briefly describe the evolution of online research guides; identify reasons for the proliferation of Springshare’s product in academic libraries; question whether LibGuides improve learning or reinforce information inequality in higher education; and propose a way to move beyond LibGuides.

An online daily diary study of alcohol use using Amazon's mechanical turk

Introduction and Aims: In recent years, unprecedented levels of Internet access and the widespread growth of emergent communication technologies have resulted in significantly greater population access for substance use researchers. Despite the research potential of such technologies, the use of the Internet to recruit individuals for participation in event-level research has been limited. The purpose of this paper is to provide a brief account of the methods and results from an online daily diary study of alcohol use. Design and Methods: Participants were recruited using Amazon's Mechanical Turk. Eligible participants completed a brief screener assessing demographics and health behaviours, with a subset of individuals subsequently recruited to participate in a 2 week daily diary study of alcohol use. Results: Multilevel models of the daily alcohol data derived from the Mechanical Turk sample (n=369) replicated several findings commonly reported in daily diary studies of alcohol use. Discussion and Conclusions: Results demonstrate that online participant recruitment and survey administration can be a fruitful method for conducting daily diary alcohol research. © 2014 Australasian Professional Society on Alcohol and other Drugs.

Assessing segmentation processes by click detection: online measure of statistical learning, or simple interference?

Statistical learning can be used to extract the words from continuous speech. Gómez, Bion, and Mehler (Language and Cognitive Processes, 26, 212–223, 2011) proposed an online measure of statistical learning: They superimposed auditory clicks on a continuous artificial speech stream made up of a random succession of trisyllabic nonwords. Participants were instructed to detect these clicks, which could be located either within or between words. The results showed that, over the length of exposure, reaction times (RTs) increased more for within-word than for between-word clicks. This result has been accounted for by means of statistical learning of the between-word boundaries. However, even though statistical learning occurs without an intention to learn, it nevertheless requires attentional resources. Therefore, this process could be affected by a concurrent task such as click detection. In the present study, we evaluated the extent to which the click detection task indeed reflects successful statistical learning. Our results suggest that the emergence of RT differences between within- and between-word click detection is neither systematic nor related to the successful segmentation of the artificial language. Therefore, instead of being an online measure of learning, the click detection task seems to interfere with the extraction of statistical regularities.