TY - JOUR A1 - Garcia, A. L. A1 - Steiniger, J. A1 - Reich, S. C. A1 - Weickert, M. O. A1 - Harsch, I. A1 - Machowetz, A. A1 - Mohlig, M. A1 - Spranger, Joachim A1 - Rudovich, N. N. A1 - Meuser, F. A1 - Doerfer, J. A1 - Katz, N. A1 - Speth, M. A1 - Zunft, Hans-Joachim Franz A1 - Pfeiffer, Andreas F. H. A1 - Koebnick, Corinna T1 - Arabinoxylan fibre consumption improved glucose metabolism, but did not affect serum adipokines in subjects with impaired glucose tolerance JF - Hormone and metabolic research N2 - The consumption of arabinoxylan, a soluble fibre fraction, has been shown to improve glycemic control in type 2 diabetic subjects. Soluble dietary fibre may modulate gastrointestinal or adipose tissue hormones regulating food intake. The present study investigated the effects of arabinoxylan consumption on serum glucose, insulin, lipids, leptin, adiponectin and resistin in subjects with impaired glucose tolerance. In a randomized, single-blind, controlled, crossover intervention trial, 11 adults consumed white bread rolls as either placebo or supplemented with 15g arabinoxylan for 6 weeks with a 6-week washout period. Fasting serum glucose, insulin, triglycerides, unesterified fatty acids, apolipoprotein A1 and B, adiponectin, resistin and leptin were assessed before and after intervention. Fasting serum glucose, serum triglycerides and apolipoprotein A-1 were significantly lower during arabinoxylan consumption compared to placebo (p = 0.029, p = 0.047; p = 0.029, respectively). No effects of arabinoxylan were observed for insulin, adiponectin, leptin and resistin as well as for apolipoprotein B, and unesterified fatty acids. In conclusion, the consumption of AX in subjects with impaired glucose tolerance improved fasting serum glucose, and triglycerides. However, this beneficial effect was not accompanied by changes in fasting adipokine concentrations. KW - dietary fibre KW - arabinoxylan KW - adiponectin KW - resistin KW - leptin Y1 - 2006 U6 - https://doi.org/10.1055/s-2006-955089 SN - 0018-5043 VL - 38 IS - 2 SP - 761 EP - 766 PB - Thieme CY - Stuttgart ER - TY - JOUR A1 - Munnes, Stefan A1 - Harsch, Corinna A1 - Knobloch, Marcel A1 - Vogel, Johannes S. A1 - Hipp, Lena A1 - Schilling, Erik T1 - Examining Sentiment in Complex Texts. A Comparison of Different Computational Approaches JF - Frontiers in Big Data N2 - Can we rely on computational methods to accurately analyze complex texts? To answer this question, we compared different dictionary and scaling methods used in predicting the sentiment of German literature reviews to the "gold standard " of human-coded sentiments. Literature reviews constitute a challenging text corpus for computational analysis as they not only contain different text levels-for example, a summary of the work and the reviewer's appraisal-but are also characterized by subtle and ambiguous language elements. To take the nuanced sentiments of literature reviews into account, we worked with a metric rather than a dichotomous scale for sentiment analysis. The results of our analyses show that the predicted sentiments of prefabricated dictionaries, which are computationally efficient and require minimal adaption, have a low to medium correlation with the human-coded sentiments (r between 0.32 and 0.39). The accuracy of self-created dictionaries using word embeddings (both pre-trained and self-trained) was considerably lower (r between 0.10 and 0.28). Given the high coding intensity and contingency on seed selection as well as the degree of data pre-processing of word embeddings that we found with our data, we would not recommend them for complex texts without further adaptation. While fully automated approaches appear not to work in accurately predicting text sentiments with complex texts such as ours, we found relatively high correlations with a semiautomated approach (r of around 0.6)-which, however, requires intensive human coding efforts for the training dataset. In addition to illustrating the benefits and limits of computational approaches in analyzing complex text corpora and the potential of metric rather than binary scales of text sentiment, we also provide a practical guide for researchers to select an appropriate method and degree of pre-processing when working with complex texts. KW - sentiment analysis KW - German literature KW - dictionary KW - word embeddings KW - automated text analysis KW - computer-assisted text analysis KW - scaling method Y1 - 2022 U6 - https://doi.org/10.3389/fdata.2022.886362 SN - 2624-909X VL - 5 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Schilling, Erik A1 - Harsch, Corinna A1 - Hipp, Lena A1 - Knobloch, Marcel A1 - Munnes, Stefan A1 - Vogel, Johannes S. T1 - Wer wird nominiert, wer gewinnt? T1 - Who gets nominated, who wins? BT - eine empirisch-vergleichende Analyse von Literaturpreisen im deutschsprachigen Raum BT - an empirical and comparative analysis of literary awards in German-speaking countries JF - Zeitschrift für Literaturwissenschaft und Linguistik N2 - Wir nehmen eine vergleichende Untersuchung der Nominierten und Preisträger:innen von sieben Buchpreisen im deutschsprachigen Raum vor, die mit einer vorab veröffentlichten Long- und/oder Shortlist arbeiten. Dazu vergleichen wir die Preise in Bezug auf soziodemographische Faktoren der Autor:innen (Geschlecht, Alter und Muttersprache), deren Bekanntheit zum Zeitpunkt der Nominierung (Aufrufe auf Wikipedia), die Anzahl vorheriger Nominierungen der Autor:innen für den gleichen Buchpreis, die ›Qualität‹ der ausgezeichneten Bücher (Anzahl der Rezensionen des nominierten Buches, positive bzw. negative Beurteilung in Rezensionen sowie die Einigkeit der Rezensent:innen darüber), das Ansehen der Verlage und die Geschlechterzusammensetzung der Jurys. Der Analysezeitraum umfasst 15 Jahre. Unser Datensatz beinhaltet Informationen zu 428 Autor:innen mit insgesamt 627 zwischen den Jahren 2005 und 2020 nominierten Büchern und 2.469 Rezensionen zu diesen Büchern. Der Datensatz wurde mittels mehrerer Methoden (z. B. Web-Scraping, Hand-Kodierung, Expert:innenbewertungen) aus verschiedenen Quellen (z. B. Web-Daten, Bibliothekskataloge, Expert:innenbewertungen) zusammengestellt. Auf diese Weise können wir unter anderem zeigen, dass für alle untersuchten Preise überwiegend deutsche Muttersprachler:innen mit gut rezensierten Büchern aus renommierten Verlagen nominiert werden und die Preise gewinnen. N2 - We undertake a comparative study of the nominees and winners of seven book awards in German-speaking countries that use a pre-published longlist and/or shortlist. To do this, we compare the awards in terms of the authors’ socio-demographic factors (gender, age, and native language), their prominence at the time of nomination (views on Wikipedia), the number of the authors’ previous nominations for the same book award, the ›quality‹ of the winning books (number of reviews of the nominated book, positive or negative assessment in reviews, and the reviewers’ unanimity about it), the reputation of the publishers, and the gender composition of the juries. The time period of analysis is 15 years. Our dataset includes information on 428 authors with a total of 627 nominated books and 2,469 reviews of these books. The dataset was compiled using several methods (e.g., web scraping, hand coding, expert reviews) from different sources (e.g., web data, library catalogs, expert reviews). This allows us to show, among other things, that for all the prizes studied, mostly German native speakers with well-reviewed books from reputable publishers are nominated and win the prizes. KW - Literaturpreise KW - Literaturkritik KW - Literaturbetrieb KW - literarisches Feld KW - symbolisches Kapital KW - Literatursoziologie KW - Soziodemographische Analyse KW - Digital Humanities KW - empirische Literaturwissenschaft KW - literary awards KW - literary criticism KW - literary scene KW - literary field KW - symbolic capital KW - sociology of literature KW - socio-demographic analysis KW - digital humanities KW - empirical literary studies Y1 - 2024 U6 - https://doi.org/10.1007/s41244-024-00321-w SN - 0049-8653 VL - 54 IS - 1 SP - 125 EP - 144 PB - Springer International Publishing CY - Cham ER -