Extracting predictive models from marked-p free-text documents at the Royal Botanic Gardens, Kew, London

In this paper we explore the combination of text-mining, un-supervised and supervised learning to extract predictive models from a corpus of digitised historical floras. These documents deal with the nomenclature, geographical distribution, ecology and comparative morphology of the species of a region. Here we exploit the fact that portions of text in the floras are marked up as different types of trait and habitat. We infer models from these different texts that can predict different habitat-types based upon the traits of plant species. We also integrate plant taxonomy data in order to assist in the validation of our models. We have shown that by clustering text describing the habitat of different floras we can identify a number of important and distinct habitats that are associated with particular families of species along with statistical significance scores. We have also shown that by using these discovered habitat-types as labels for supervised learning we can predict them based upon a subset of traits, identified using wrapper feature selection

A hashtag worth a thousand words: Discursive strategies around #JeNeSuisPasCharlie after the 2015 Charlie Hebdo shooting

Following a shooting attack by two self-proclaimed Islamist gunmen at the offices of French satirical weekly Charlie Hebdo on 7 January 2015, there emerged the hashtag #JeSuisCharlie on Twitter as an expression of solidarity and support for the magazine’s right to free speech. Almost simultaneously, however, there was also #JeNeSuisPasCharlie explicitly countering the former, affirmative hashtag. Based on a multimethod analysis of 74,047 tweets containing #JeNeSuisPasCharlie posted between 7 and 11 January, this article reveals that users of the hashtag under study employed various discursive strategies and tactics to challenge the mainstream framing of the shooting as the universal value of freedom of expression being threatened by religious extremism, while protecting themselves from the risk of being viewed as disrespecting victims or endorsing the violence committed. The significance of this study is twofold. First, it extends the literature on strategic speech acts by examining how such acts take place in a social media context. Second, it highlights the need for a multidimensional and reflective methodology when dealing with data mined from social media

Optimal and Automated Deployment for Microservices

Microservices are highly modular and scalable Service Oriented Architectures. They underpin automated deployment practices like Continuous Deployment and Autoscaling. In this paper, we formalize these practices and show that automated deployment - proven undecidable in the general case - is algorithmically treatable for microservices. Our key assumption is that the configuration life-cycle of a microservice is split into two phases: (i) creation, which entails establishing initial connections with already available microservices, and (ii) subsequent binding/unbinding with other microservices. To illustrate the applicability of our approach, we implement an automatic optimal deployment tool and compute deployment plans for a realistic microservice architecture, modeled in the Abstract Behavioral Specification (ABS) language

How Digital Are the Digital Humanities? An Analysis of Two Scholarly Blogging Platforms

In this paper we compare two academic networking platforms, HASTAC and Hypotheses, to show the distinct ways in which they serve specific communities in the Digital Humanities (DH) in different national and disciplinary contexts. After providing background information on both platforms, we apply co-word analysis and topic modeling to show thematic similarities and differences between the two sites, focusing particularly on how they frame DH as a new paradigm in humanities research. We encounter a much higher ratio of posts using humanities-related terms compared to their digital counterparts, suggesting a one-way dependency of digital humanities-related terms on the corresponding unprefixed labels. The results also show that the terms digital archive, digital literacy, and digital pedagogy are relatively independent from the respective unprefixed terms, and that digital publishing, digital libraries, and digital media show considerable cross-pollination between the specialization and the general noun. The topic modeling reproduces these findings and reveals further differences between the two platforms. Our findings also indicate local differences in how the emerging field of DH is conceptualized and show dynamic topical shifts inside these respective contexts