@inproceedings{54513,
  abstract     = {{Learning argumentative writing is challenging. Besides writing fundamentals such as syntax and grammar, learners must select and arrange argument components meaningfully to create high-quality essays. To support argumentative writing computationally, one step is to mine the argumentative structure. When combined with automatic essay scoring, interactions of the argumentative structure and quality scores can be exploited for comprehensive writing support. Although studies have shown the usefulness of using information about the argumentative structure for essay scoring, no argument mining corpus with ground-truth essay quality annotations has been published yet. Moreover, none of the existing corpora contain essays written by school students specifically. To fill this research gap, we present a German corpus of 1,320 essays from school students of two age groups. Each essay has been manually annotated for argumentative structure and quality on multiple levels of granularity. We propose baseline approaches to argument mining and essay scoring, and we analyze interactions between both tasks, thereby laying the ground for quality-oriented argumentative writing support.}},
  author       = {{Stahl, Maja and Michel, Nadine and Kilsbach, Sebastian and Schmidtke, Julian  and Rezat, Sara and Wachsmuth, Henning}},
  keywords     = {{Annotation, Corpus, Argumentative Structure}},
  title        = {{{A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality}}},
  doi          = {{10.48550/arXiv.2404.02529}},
  year         = {{2024}},
}

@inproceedings{1135,
  abstract     = {{In this paper, we describe our system developed for the GErman SenTiment AnaLysis shared Task (GESTALT) for participation in the Maintask 2: Subjective Phrase and Aspect Extraction from Product Reviews. We present a tool, which identifies subjective and aspect phrases in German product reviews. For the recognition of subjective phrases, we pursue a lexicon-based approach. For the extraction of aspect phrases from the reviews, we consider two possible ways: Besides the subjectivity and aspect look-up, we also implemented a method to establish which subjective phrase belongs to which aspect. The system achieves better results for the recognition of aspect phrases than for the subjective identification.}},
  author       = {{Dollmann, Markus and Geierhos, Michaela}},
  booktitle    = {{Workshop Proceedings of the 12th Edition of the KONVENS Conference}},
  editor       = {{Faaß, Gertrud and Ruppenhofer, Josef}},
  isbn         = {{978-3-934105-47-8}},
  keywords     = {{corpus linguistics, sentiment analysis}},
  location     = {{Hildesheim, Germany}},
  pages        = {{185--191}},
  publisher    = {{Universitätsverlag Hildesheim}},
  title        = {{{SentiBA: Lexicon-based Sentiment Analysis on German Product Reviews}}},
  year         = {{2014}},
}