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Wiktionary is increasingly gaining influence in a wide variety of linguistic fields such as NLP and lexicography, and has great potential to become a serious competitor for publisher-based and academic dictionaries. However, little is known about the "crowd" that is responsible for the content of Wiktionary. In this article, we want to shed some light on selected questions concerning large-scale cooperative work in online dictionaries. To this end, we use quantitative analyses of the complete edit history files of the English and German Wiktionary language editions. Concerning the distribution of revisions over users, we show that — compared to the overall user base — only very few authors are responsible for the vast majority of revisions in the two Wiktionary editions. In the next step, we compare this distribution to the distribution of revisions over all the articles. The articles are subsequently analysed in terms of rigour and diversity, typical revision patterns through time, and novelty (the time since the last revision). We close with an examination of the relationship between corpus frequencies of headwords in articles, the number of article visits, and the number of revisions made to articles.
We present an empirical study addressing the question whether, and to which extent, lexicographic writing aids improve text revision results. German university students were asked to optimise two German texts using (1) no aids at all, (2) highlighted problems, or (3) highlighted problems accompanied by lexicographic resources that could be used to solve the specific problems. We found that participants from the third group corrected the largest number of problems and introduced the fewest semantic distortions during revision. Also, they reached the highest overall score and were most efficient (as measured in points per time). The second group with highlighted problems lies between the two other groups in almost every measure we analysed. We discuss these findings in the scope of intelligent writing environments, the effectiveness of writing aids in practical usage situations and teaching dictionary skills.
The author presents a study using eye-tracking-while-reading data from participants reading German jurisdictional texts. I am particularly interested in nominalisations. It can be shown that nominalisations are read significantly longer than other nouns and that this effect is quite strong. Furthermore, the results suggest that nouns are read faster in reformulated texts. In the reformulations, nominalisations were transformed into verbal structures. Reformulations did not lead to increased processing times of verbal constructions but reformulated texts were read faster overall. Where appropriate, results are compared to a previous study of Hansen et al. (2006) using the same texts but other methodology and statistical analysis.