Languages employ different strategies to transmit structural and grammatical information. While, for example, grammatical dependency relationships in sentences are mainly conveyed by the ordering of the words for languages like Mandarin Chinese, or Vietnamese, the word ordering is much less restricted for languages such as Inupiatun or Quechua, as these languages (also) use the internal structure of words (e.g. inflectional morphology) to mark grammatical relationships in a sentence. Based on a quantitative analysis of more than 1,500 unique translations of different books of the Bible in almost 1,200 different languages that are spoken as a native language by approximately 6 billion people (more than 80% of the world population), we present large-scale evidence for a statistical trade-off between the amount of information conveyed by the ordering of words and the amount of information conveyed by internal word structure: languages that rely more strongly on word order information tend to rely less on word structure information and vice versa. Or put differently, if less information is carried within the word, more information has to be spread among words in order to communicate successfully. In addition, we find that–despite differences in the way information is expressed–there is also evidence for a trade-off between different books of the biblical canon that recurs with little variation across languages: the more informative the word order of the book, the less informative its word structure and vice versa. We argue that this might suggest that, on the one hand, languages encode information in very different (but efficient) ways. On the other hand, content-related and stylistic features are statistically encoded in very similar ways.

Abstract:In this paper, we use the 2012 log files of two German online dictionaries (Digital Dictionary of the German Language1 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 dass Information readily available in Wiktionary into our analysis to improve our results considerably.

We present studies using the 2013 log files from the German version of Wiktionary. We investigate several lexicographically relevant variables and their effect on look-up frequency: Corpus frequency of the headword seems to have a strong effect on the number of visits to a Wiktionary entry. We then consider the question of whether polysemic words are looked up more often than monosemic ones. Here, we also have to take into account that polysemic words are more frequent in most languages. Finally, we present a technique to investigate the time-course of look-up behaviour for specific entries. We exemplify the method by investigating influences of (temporary) social relevance of specific headwords.

The article presents the results of a survey on dictionary use in Europe, focusing on general monolingual dictionaries. The survey is the broadest survey of dictionary use to date, covering close to 10,000 dictionary users (and non-users) in nearly thirty countries. Our survey covers varied user groups, going beyond the students and translators who have tended to dominate such studies thus far. The survey was delivered via an online survey platform, in language versions specific to each target country. It was completed by 9,562 respondents, over 300 respondents per country on average. The survey consisted of the general section, which was translated and presented to all participants, as well as country-specific sections for a subset of 11 countries, which were drafted by collaborators at the national level. The present report covers the general section. IntroductionResearch into dictionary use has become increasingly important in recent years. In contrast to 15 years ago, new findings in this area are presented every year, e.g. at every Euralex or eLex conference. These studies range from questionnaire or log file studies to smaller-scale studies focussing on eye tracking, usability, or other aspects of dictionary use measurable in a lab. For an overview of different studies,

Recently, it was demonstrated that generalized entropies of order α offer novel and important opportunities to quantify the similarity of symbol sequences where α is a free parameter. Varying this parameter makes it possible to magnify differences between different texts at specific scales of the corresponding word frequency spectrum. For the analysis of the statistical properties of natural languages, this is especially interesting, because textual data are characterized by Zipf’s law, i.e., there are very few word types that occur very often (e.g., function words expressing grammatical relationships) and many word types with a very low frequency (e.g., content words carrying most of the meaning of a sentence). Here, this approach is systematically and empirically studied by analyzing the lexical dynamics of the German weekly news magazine Der Spiegel (consisting of approximately 365,000 articles and 237,000,000 words that were published between 1947 and 2017). We show that, analogous to most other measures in quantitative linguistics, similarity measures based on generalized entropies depend heavily on the sample size (i.e., text length). We argue that this makes it difficult to quantify lexical dynamics and language change and show that standard sampling approaches do not solve this problem. We discuss the consequences of the results for the statistical analysis of languages.

Abstract: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 publisherbased 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. Keywords: USER-GENERATED

In order to demonstrate why it is important to correctly account for the (serial dependent) structure of temporal data, we document an apparently spectacular relationship between population size and lexical diversity: for five out of seven investigated languages, there is a strong relationship between population size and lexical diversity of the primary language in this country. We show that this relationship is the result of a misspecified model that does not consider the temporal aspect of the data by presenting a similar but nonsensical relationship between the global annual mean sea level and lexical diversity. Given the fact that in the recent past, several studies were published that present surprising links between different economic, cultural, political and (socio-)demographical variables on the one hand and cultural or linguistic characteristics on the other hand, but seem to suffer from exactly this problem, we explain the cause of the misspecification and show that it has profound consequences. We demonstrate how simple transformation of the time series can often solve problems of this type and argue that the evaluation of the plausibility of a relationship is important in this context. We hope that our paper will help both researchers and reviewers to understand why it is important to use special models for the analysis of data with a natural temporal ordering.

To design effective electronic dictionaries, reliable empirical information on how dictionaries are actually being used is of great value for lexicographers. To my knowledge, no existing empirical research addresses the context of dictionary use, or, in other words, the extra-lexicographic situations in which a dictionary consultation is embedded. This is mainly due to the fact that data about these con texts are difficult to obtain. To take a first step in closing this research gap, we in corporated an open-ended question ("In which contexts or situations would you use a dictionary?") into our first online survey (N = 684). Instead of presenting wellknown facts about standardized types of usage situation, this chapter will focus on the more offbeat circumstances of dictionary use and aims of users, as they are re flected in the responses. Overall, my results indicate that there is a community whose work is closely linked with dictionaries. Dictionaries are also seen as a lin guistic treasure trove for games or crossword puzzles, and as a standard which can be referred to as an authority. While it is important to emphasize that my results are only preliminary, they do indicate the potential of empirical research in this area.