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Transforming the current rather centralized electricity generating system into a climate neutral system based on renewable energy is an important approach to reduce greenhouse gas emissions and thus mitigate climate change. Stakeholders have each of them their own perception of the best strategies to achieve such a transformation. All perspectives are equally legitimate and needed for developing a specific transformation strategy suited for the region in focus....
The Emotions of London
(2016)
A few years ago, a group formed by Ben Allen, Cameron Blevins, Ryan Heuser, and Matt Jockers decided to use topic modeling to extract geographical information from nineteenth-century novels. Though the study was eventually abandoned, it had revealed that London-related topics had become significantly more frequent in the course of the century, and when some of us were later asked to design a crowd-sourcing experiment, we decided to add a further dimension to those early findings, and see whether London place-names could become the cornerstone for an emotional geography of the city.
Literature, measured
(2016)
There comes a moment, in digital humanities talks, when someone raises the hand and says: "Ok. Interesting. But is it really new?" Good question... And let's leave aside the obvious lines of defense, such as "but the field is still only at its beginning!", or "and traditional literary criticism, is that always new?" All true, and all irrelevant; because the digital humanities have presented themselves as a radical break with the past, and must therefore produce evidence of such a break. And the evidence, let's be frank, is not strong. What is there, moreover, comes in a variety of forms, beginning with the slightly paradoxical fact that, in a new approach, not everything has to be new. When "Network Theory, Plot Analysis” pointed out, in passing, that a network of Hamlet had Hamlet at its center, the New York Times gleefully mentioned the passage as an unmistakable sign of stupidity. Maybe; but the point, of course, was not to present Hamlet’s centrality as a surprise; it was exactly the opposite: had the new approach not found Hamlet at the center of the play, its plausibility would have disintegrated. Before using network theory for dramatic analysis, I had to test it, and prove that it corroborated the main results of previous research.
The Multilingual Assessment Instrument for Narratives (MAIN) was designed in order to assess narrative skills in children who acquire one or more languages from birth or from early age. MAIN is suitable for children from 3 to 10 years and evaluates both comprehension and production of narratives. Its design allows for the assessment of several languages in the same child, as well as for different elicitation modes: Model Story, Retelling, and Telling. MAIN contains four parallel stories, each with a carefully designed six-picture sequence. The stories are controlled for cognitive and linguistic complexity, parallelism in macrostructure and microstructure, as well as for cultural appropriateness and robustness. The instrument has been developed on the basis of extensive piloting with more than 550 monolingual and bilingual children aged 3 to 10, for 15 different languages and language combinations. Even though MAIN has not been norm-referenced yet, its standardized procedures can be used for evaluation, intervention and research purposes. MAIN is currently available in the following languages: English, Afrikaans, Albanian, Basque, Bulgarian, Croatian, Cypriot Greek, Danish, Dutch, Estonian, Finnish, French, German, Greek, Hebrew, Icelandic, Italian, Lithuanian, Norwegian, Polish, Russian, Spanish, Standard Arabic, Swedish, Turkish, Vietnamese, and Welsh.
The Shared Task on Source and Target Extraction from Political Speeches (STEPS) first ran in 2014 and is organized by the Interest Group on German Sentiment Analysis (IGGSA). This volume presents the proceedings of the workshop of the second iteration of the shared task. The workshop was held at KONVENS 2016 at Ruhr-University Bochum on September 22, 2016.
As in the first edition of the shared task the main focus of STEPS was on fine-grained sentiment analysis and offered a full task as well as two subtasks for the extraction Subjective Expressions and/or their respective Sources and Targets.
In order to make the task more accessible, the annotation schema was revised for this year’s edition and an adjudicated gold standard was used for the evaluation. In contrast to the pilot task, this iteration provided training data for the participants, opening the Shared Task for systems based on machine learning approaches.
The gold standard1 as well as the evaluation tool2 have been made publicly available to the research community via the STEPS’ website.
We would like to thank the GSCL for their financial support in annotating the 2014 test data, which were available as training data in this iteration. A special thanks also goes to Stephanie Köser for her support on preparing and carrying out the annotation of this year’s test data. Finally, we would like to thank all the participants for their contributions and discussions at the workshop.
NLP4CMC III : 3rd workshop on natural language processing for computer-mediated communication
(2016)
The present paper reports the first results of the compilation and annotation of a blog corpus for German. The main aim of the project is the representation of the blog discourse structure and relations between its elements (blog posts, comments) and participants (bloggers, commentators). The data included in the corpus were manually collected from the scientific blog portal SciLogs. The feature catalogue for the corpus annotation includes three types of information which is directly or indirectly provided in the blog or can be construed by means of statistical analysis or computational tools. At this point, only directly available information (e.g., title of the blog post, name of the blogger etc.) has been annotated. We believe, our blog corpus can be of interest for the general study of blog structure or related research questions as well as for the development of NLP methods and techniques (e.g. for authorship detection).