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In the present contribution, I investigate if and how the English and French editions of the Wiktionary collaborative dictionary can be used as a corpus for real time neology watch. This option is envisaged as a stopgap, when no satisfactory corpus is available. Wiktionary can also prove useful in addition to standard corpus analysis, to minimize the risk of overlooking new coinages and new senses. Since the collaborative dictionary’s quest for exhaustiveness makes the manual inspection of the new additions unreasonable (more than 31,000 English lemmas and 11,000 French lemmas entered the nomenclature in 2020), identifying the possibly relevant headwords is an issue. The solution proposed here is to use Wiktionary revision history to detect the (new or existing) entries that received the greatest number of modifications. The underlying hypothesis is that the most heavily edited pages can help identify the vocabulary related to “hot topics”, assuming that, in 2020, the pandemic-related vocabulary ranks high. I used two measures introduced by Lih (2004), whose aim was to estimate the quality of Wikipedia articles: the so-called rigour (number of edits per page) and diversity (number of unique contributors per page). In the present study, I propose to adapt the rigour and diversity metrics to Wiktionary in order to identify the pages that generated a particular stir, rather than to estimate the quality of the articles. I do not subscribe to the idea that – in Wiktionary – more revisions necessarily produce quality articles (more revisions often produce complete articles). I therefore adopt Lih’s notion of diversity to refer to the number of distinct contributors, but leave out the name rigour when it comes to the number of revisions. Wolfer and Müller-Spitzer (2016) used the two metrics to describe the dynamics of the German and English editions of Wiktionary. One of their findings was that the number of edits per page is correlated with corpus word frequencies. The variation in number of page edits should therefore reflect to some extent the variation of corpus word frequencies. Renouf (2013) established a relationship between the fluctuation of word frequencies in a diachronic corpus and various neological processes. In particular, she illustrated how specific events generate sudden frequency spikes for words previously unseen in the corpus. For instance, Eyjafjallajökull, the – existing – name of an Icelandic glacier, appeared in the corpus when the underlying volcano erupted in 2010 and disrupted air traffic in Europe. In order to check if the same phenomenon occurs when using Wiktionary edits instead of corpus frequencies, I manually annotated the most frequently revised entries (according to various ranking scores) with the binary tag: “related to Covid-19” (yes/no). The annotations were then used to test the ability of various configurations to detect relevant headwords from the English and French Wiktionary, namely Covid-19 neologisms and related existing words that deserve updates.
This paper presents the main issues connected with the creation of a trilingual Hungarian-Italian-English dictionary of the COVID-19 pandemic using Lexonomy. My aim is not only to create a coronacorpus (in Hungarian, I propose my own corona-neologism or ‘coroneologism’: koronakorpusz) and a dictionary of equivalents, but also to understand how the different waves and phases of the COVID-19 pandemic are changing the Hungarian language, detect the Corona-, COVID-, pandemic-, virus-, mask-, quarantine-, and vaccine-related neologisms, and offer an overview of the most frequent or linguistically interesting Hungarian neologisms and multiword units related to COVID-19.
Since the beginning of 2020, the Covid-19 pandemic has dominated public discourse and introduced a wealth of words and expressions to the general vocabulary of English and other world languages. The lexical adaptation necessitated by this global health crisis has been unprecedented in speed and scope, and in response, the Oxford English Dictionary (OED) has continually revised its coverage, publishing special updates of Covid-19-related words in 2020 outside of its usual quarterly publication cycle. This article describes how OED lexicographers have analysed language corpora and other text databases to monitor the development of pandemic-related words and provide a linguistic and historical context to their usage.
Preface
(2015)
Based on specific linguistic landmarks in the speech signal, this study investigates pitch level and pitch span differences in English, German, Bulgarian and Polish. The analysis is based on 22 speakers per language (11 males and 11 females). Linear mixed models were computed that include various linguistic measures of pitch level and span, revealing characteristic differences across languages and between language groups. Pitch level appeared to have significantly higher values for the female speakers in the Slavic than the Germanic group. The male speakers showed slightly different results, with only the Polish speakers displaying significantly higher mean values for pitch level than the German males. Overall, the results show that the Slavic speakers tend to have a wider pitch span than the German speakers. But for the linguistic measure, namely for span between the initial peaks and the non-prominent valleys, we only find the difference between Polish and German speakers. We found a flatter intonation contour in German than in Polish, Bulgarian and English male and female speakers and differences in the frequency of the landmarks between languages. Concerning “speaker liveliness” we found that the speakers from the Slavic group are significantly livelier than the speakers from the Germanic group.
This study investigates cross-language differences in pitch range and variation in four languages from two language groups: English and German (Germanic) and Bulgarian and Polish (Slavic). The analysis is based on large multi-speaker corpora (48 speakers for Polish, 60 for each of the other three languages). Linear mixed models were computed that include various distributional measures of pitch level, span and variation, revealing characteristic differences across languages and between language groups. A classification experiment based on the relevant parameter measures (span, kurtosis and skewness values for pitch distributions for each speaker) succeeded in separating the language groups.
Freezing in it-clefts
(2013)
The paper contributes to the raising vs. control debate with respect to modals through (A) novel data; (B) the investigation of a domain in which it has proven particularly problematic: volitional modality. We analyze oblique arguments of experiencer verbs embedded under German wollen ‘want’ and propose that they support both generalized raising and the abandonment of the classical version of the Theta Criterion. Byproducts of the analysis include a syntactic account involved in a class of datives in the language together with the initial characterization of a related modal in German which is expressed through the same item as volition and which we term weak.