Using State-of-the-art Emotion Detection Models in a Crisis Communication Context

Times of crisis are usually associated with highly emotional experiences, which often result in emotionally charged communication. This is especially the case on social media. Identifying the emotional climate on social media is imperative in the context of crisis communication, e.g., in view of shaping crisis response strategies. However, the sheer volume of social media data often makes manual oversight impossible. In this paper, we therefore investigate how automatic methods for emotion detection can aid research on crisis communication and social media. Concretely, we investigate two Dutch emotion detection models (a transformer model and a classical machine learning model based on dictionaries) and apply them to Dutch tweets about four different crisis cases. First, we perform a validation study to assess the performance of these models in the domain of crisis-related tweets. Secondly, we propose a framework for monitoring the emotional climate on social media, and assess whether emotion detection models can be used to address the steps in the framework

The SASSCAL contribution to climate observation, climate data management and data rescue in Southern Africa

A major task of the newly established "Southern African Science Service Centre for Climate Change and Adaptive Land Management" (SASSCAL; www.sasscal.org) and its partners is to provide science-based environmental information and knowledge which includes the provision of consistent and reliable climate data for Southern Africa. Hence, SASSCAL, in close cooperation with the national weather authorities of Angola, Botswana, Germany and Zambia as well as partner institutions in Namibia and South Africa, supports the extension of the regional meteorological observation network and the improvement of the climate archives at national level. With the ongoing rehabilitation of existing weather stations and the new installation of fully automated weather stations (AWS), altogether 105 AWS currently provide a set of climate variables at 15, 30 and 60 min intervals respectively. These records are made available through the SASSCAL WeatherNet, an online platform providing near-real time data as well as various statistics and graphics, all in open access. This effort is complemented by the harmonization and improvement of climate data management concepts at the national weather authorities, capacity building activities and an extension of the data bases with historical climate data which are still available from different sources. These activities are performed through cooperation between regional and German institutions and will provide important information for climate service related activities

Measuring text simplification with the crowd

Text can often be complex and difficult to read, especially for peo ple with cognitive impairments or low literacy skills. Text simplifi cation is a process that reduces the complexity of both wording and structure in a sentence, while retaining its meaning. However, this is currently a challenging task for machines, and thus, providing effective on-demand text simplification to those who need it re mains an unsolved problem. Even evaluating the simplicity of text remains a challenging problem for both computers, which cannot understand the meaning of text, and humans, who often struggle to agree on what constitutes a good simplification. This paper focuses on the evaluation of English text simplifica tion using the crowd. We show that leveraging crowds can result in a collective decision that is accurate and converges to a consen sus rating. Our results from 2,500 crowd annotations show that the crowd can effectively rate levels of simplicity. This may allow sim plification systems and system builders to get better feedback about how well content is being simplified, as compared to standard mea sures which classify content into ‘simplified ’ or ‘not simplified’ categories. Our study provides evidence that the crowd could be used to evaluate English text simplification, as well as to create simplified text in future work

Stronger diversity effects with increased environmental stress : a study of multitrophic interactions between oak, powdery mildew and ladybirds

Recent research has suggested that increasing neighbourhood tree species diversity may mitigate the impact of pests or pathogens by supporting the activities of their natural enemies and/or reducing the density of available hosts. In this study, we attempted to assess these mechanisms in a multitrophic study system of young oak (Quercus), oak powdery mildew (PM, caused by Erysiphe spp.) and a mycophagous ladybird (Psyllobora vigintiduo-punctata). We assessed ladybird mycophagy on oak PM in function of different neighbourhood tree species compositions. We also evaluated whether these species interactions were modulated by environmental conditions as suggested by the Stress Gradient Hypothesis. We adopted a complementary approach of a field experiment where we monitored oak saplings subjected to a reduced rainfall gradient in a young planted forest consisting of different tree species mixtures, as well as a lab experiment where we independently evaluated the effect of different watering treatments on PM infections and ladybird mycophagy. In the field experiment, we found effects of neighbourhood tree species richness on ladybird mycophagy becoming more positive as the target trees received less water. This effect was only found as weather conditions grew drier. In the lab experiment, we found a preference of ladybirds to graze on infected leaves from trees that received less water. We discuss potential mechanisms that might explain this preference, such as emissions of volatile leaf chemicals. Our results are in line with the expectations of the Natural Enemies Hypothesis and support the hypothesis that biodiversity effects become stronger with increased environmental stress

e-Surveillance in animal health : use and evaluation of mobile tools

In the last decade, mobile technology offered new opportunities and challenges in animal health surveillance. It began with the use of basic mobile phones and short message service (SMS) for disease reporting, and the development of smartphones and other mobile tools has expanded the possibilities for data collection. These tools assist in the collection of data as well as geo-referenced mapping of diseases, and mapping, visualization and identification of vectors such as ticks. In this article we share our findings about new technologies in the domain of animal health surveillance, based on several projects using a wide range of mobile tools, each with their specific applicability and limitations. For each of the tools used, a comprehensive overview is given about its applicability, limitations, technical requirements, cost and also the perception of the users.The evaluation of the tools clearly shows the importance of selecting the appropriate tool depending on the envisaged data to be collected. Accessibility, visualization and cost related to data collection differ significantly among the tools tested. This paper can thus be seen as a practical guide to the currently available tools.The authors would like to thank the Belgian Science Policy Office (BELSPO) for their financial support of the Stereo II project entitled TickRisk (SR/00/144). Also the Belgian Development Cooperation (DGD) is thanked for their financial support of the FA3 programme. The syndromic livestock disease surveillance in Kenya was supported by the Wellcome Trust, UK (grant number 081828/B/06/Z) and the Compton Foundation, USA.http://journals.cambridge.org/action/displayJournal?jid=PARab201

Detecting a stochastic gravitational wave background with the Laser Interferometer Space Antenna

The random superposition of many weak sources will produce a stochastic background of gravitational waves that may dominate the response of the LISA (Laser Interferometer Space Antenna) gravitational wave observatory. Unless something can be done to distinguish between a stochastic background and detector noise, the two will combine to form an effective noise floor for the detector. Two methods have been proposed to solve this problem. The first is to cross-correlate the output of two independent interferometers. The second is an ingenious scheme for monitoring the instrument noise by operating LISA as a Sagnac interferometer. Here we derive the optimal orbital alignment for cross-correlating a pair of LISA detectors, and provide the first analytic derivation of the Sagnac sensitivity curve.Comment: 9 pages, 11 figures. Significant changes to the noise estimate