Impact, studies in language and society 11. 11) Includes bibliographical references and indexes. (Impact: Studies in language and society, issn 1385–7908 v.
Volume III / edited by Marlis Hellinger and Hadumod Bußmann. Library of Congress Cataloging-in-Publication Data Gender Across Languages: The linguistic representation of women and men. The paper used in this publication meets the minimum requirements of American National Standard for Information Sciences – Permanence of Paper for Printed Library Materials, ansi z39.48-1984. John Benjamins Publishing Company Amsterdam/Philadelphia Marlis Hellinger University of Frankfurt am Main
Gender Across Languages The linguistic representation of women and men volume 3 Volume 11 Gender Across Languages: The linguistic representation of women and men Volume III Edited by Marlis Hellinger and Hadumod Bußmann General editor Annick De Houwer University of Antwerp The scope of the series is broad, with special emphasis on areas such as language planning and language policies language conflict and language death language standards and language change dialectology diglossia discourse studies language and social identity (gender, ethnicity, class, ideology) and history and methods of sociolinguistics. Impact: Studies in language and society impact publishes monographs, collective volumes, and text books on topics in sociolinguistics. They suggest that Croatia and Serbia still represent the two extremes, reflecting a history of normative divergences, while Bosnia-Herzegovina and Montenegro, depending on the variable, lean to one or the other side.TITLE "Gender Across Languages: The linguistic representation of women and men. These analyses are intended to show the extent to which current state borders correspond to linguistic boundaries. This analysis is completed with a measure of variable consistency for each country. The groupings of linguistic variables and countries are calculated given the state borders and the Jensen-Shannon divergence between distributions of the 16 variables within each state.
The second analysis deals with linguistic distance between the states. These boundaries are then plotted over the state borders for a visual comparison. The first one finds boundaries in the spatial distribution of the linguistic variable levels through the kernel density estimation smoothing technique. We perform our analyses on a dataset of geo-encoded Twitter status messages collected in the period from mid-2013 to the end of 2016. In this paper we deal with the spatial distribution of 16 linguistic features known to vary between Bosnian, Croatian, Montenegrin, and Serbian.
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