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In this paper, the authors use the 2012 log files of two German online dictionaries (Digital Dictionary of the German Language and the German Version of Wiktionary) and the 100,000 most frequent words in the Mannheim German Reference Corpus from 2009 to answer the question of whether dictionary users really do look up frequent words, first asked by de Schryver et al. (2006). By using an approach to the comparison of log files and corpus data which is completely different from that of the aforementioned authors, we provide empirical evidence that indicates - contrary to the results of de Schryver et al. and Verlinde/Binon (2010) - that the corpus frequency of a word can indeed be an important factor in determining what online dictionary users look up. Finally, we incorporate word class Information readily available in Wiktionary into our analysis to improve our results considerably.
This chapter presents empirical findings on the question which criteria are making a good online dictionary using data on expectations and demands collected in the first study (N=684), completed with additional results from the second study (N=390) which examined more closely whether the respondents had differentiated views on individual aspects of the criteria rated in the first study. Our results show that the classical criteria of reference books (e.g. reliability, clarity) were rated highest by our participants, whereas the unique characteristics of online dictionaries (e.g. multimedia, adaptability) were rated and ranked as (partly) unimportant. To verify whether or not the poor rating of these innovative features was a result of the fact that the subjects are not used to online dictionaries incorporating those features, we integrated an experiment into the second study. Our results revealed a learning effect: Participants in the learning-effect condition, i. e. respondents who were first presented with examples of possible innovative features of online dictionaries,judged adaptability and multimedia to be more useful than participants who did not have this information. Thus, our data point to the conclusion that developing innovative features is worthwhile but that it is necessary to be aware of the fact that users can only be convinced of its benefits gradually.