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Comprehending conditional statements is fundamental for hypothetical reasoning about situations. However, the online comprehension of conditional statements containing different conditional connectives is still debated. We report two self-paced reading experiments on German conditionals presenting the conditional connectives wenn (‘if’) and nur wenn (‘only if’) in identical discourse contexts. In Experiment 1, participants read a conditional sentence followed by the confirmed antecedent p and the confirmed or negated consequent q. The final, critical sentence was presented word by word and contained a positive or negative quantifier (ein/kein ‘one/no’). Reading times of the two quantifiers did not differ between the two conditional connectives. In Experiment 2, presenting a negated antecedent, reading times for the critical positive quantifier (ein) did not differ between conditional connectives, while reading times for the negative quantifier (kein) were shorter for nur wenn than for wenn. The results show that comprehenders form distinct predictions about discourse continuations due to differences in the lexical semantics of the tested conditional connectives, shedding light on the role of conditional connectives in the online interpretation of conditionals in general.
We investigate the optional omission of the infinitival marker in a Swedish future tense construction. During the last two decades the frequency of omission has been rapidly increasing, and this process has received considerable attention in the literature. We test whether the knowledge which has been accumulated can yield accurate predictions of language variation and change. We extracted all occurrences of the construction from a very large collection of corpora. The dataset was automatically annotated with language-internal predictors which have previously been shown or hypothesized to affect the variation. We trained several models in order to make two kinds of predictions: whether the marker will be omitted in a specific utterance and how large the proportion of omissions will be for a given time period. For most of the approaches we tried, we were not able to achieve a better-than-baseline performance. The only exception was predicting the proportion of omissions using autoregressive integrated moving average models for one-step-ahead forecast, and in this case time was the only predictor that mattered. Our data suggest that most of the language-internal predictors do have some effect on the variation, but the effect is not strong enough to yield reliable predictions.
The question of whether a letter is a grapheme or not is a perennial issue in writing research. The answer depends on which criteria are used to differentiate between letters and graphemes and, ultimately,how the unit ‘grapheme’ is defined. This problem is particularly relevant to complex graphemes, i.e. sequences of letters that behave like a single grapheme in certain respects. Typical for German is the ‹ch›. This paper argues for a scalar concept of graphemes, which compares the grapheme status of each of the units under investigation. For this purpose, new criteria for the identification of complex graphemes are used, which originate from handwriting analysis. There, it is shown that complex graphemes are connected with each other disproportionately often and also have deviating letter forms disproportionately often.
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.
To leverage the Deaf community’s increasing online presence, the web-based platform NZSL Share was launched in March 2020 to crowdsource new and previously undocumented signs, and to encourage community validation of these signs. The platform allows users to upload sign videos, comment on videos and agree or disagree with (often new) signs being proposed. It is managed by the research team that maintains the ODNZSL, which includes the authors. NZSL Share is being used by individuals as well as Deaf community groups to record and share signs of a specialist nature (e.g., school curriculum signs). NZSL Share now has close to 50 actively contributing members. Its launch coincided with the 2020 COVID-19 outbreak in New Zealand and so some of the first signs contributed were COVID-19-related, which are the focus of this paper.
This paper arises within the current communication urgency experienced throughout the pandemic. From its onset, several new lexical units have permeated the overall media discourse, as well as social media and other channels. These units convey information to the public regarding the ‘severe acute respiratory syndrome’ namely COVID-19. In addition to its worldwide impact healthwise, the pandemic generates noteworthy influence in the linguistic landscape, and as a result, a significant number of neologisms have emerged. Within the scope of our ongoing research, we identify the neologisms in European Portuguese that are related to the term COVID-19 via form or meaning. However, not all the new lexical units identified in our corpus containing COVID-19 in its formation can unequivocally be regarded as neoterms (terminological neologisms). Accordingly, this article aims not only to reflect on the distinction between neologism and neoterm but also to explore the determinologisation process that several of these new lexical units experience.
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.
This article has a double objective. First, it seeks to offer an initial approach, with critical notes, to the group of pandemic-related neologisms incorporated into the DLE in the year 2020. To that end, the trends in the academic dictionary’s incorporation of neologisms will be reviewed, focusing in particular on specialized language neologisms. Second, the article presents the design of a research study that allows for the examination of any new words beginning with CORONA- added to the DLE and the DHLE. An assessment will be made of the particularities of the DLE and the DHLE regarding the incorporation of the new words, as well as the degree of correspondence or complementarity between the two works in this sense. This will show the complementary roles that the DLE and the DHLE are currently acquiring. In this sense, the new additions open up a debate on the treatment of neologisms in academic lexicography, in a particularly unique scenario.
This paper focuses on standardological and lexicographical aspects of Coronavirus-related neologisms in Croatian. The presented results are based on corpus analysis. The initial corpus for this analysis consists of terms collected for the Glossary of Coronavirus. This corpus has been supplemented by terms we collected on the Internet and from the media. The General Croatian corpora: Croatian Web Corpus – hrWaC (cf. Ljubešić/Klubička 2016) and Croatian Language Repository (cf. Brozović Rončević/Ćavar 2008: 173–186) were also used, but since they do not include neologisms that entered the language after 2013, they could be used only to check terms in the language before that time. From October 2021, a specialized Corona corpus compiled by Štrkalj Despot and Ostroški Anić (2021) became publicly available on request. The data from these corpora are analyzed by Sketch Engine (cf. Kilgarriff et al. 2004: 105–116), a corpus query system loaded with the corpora, enabling the display of lexeme context through concordances and (differential) word sketches and the extraction of keywords (terms) and N-grams. The most common collocations are sorted into syntactic categories. For English equivalents, in addition to the sources found on the Internet, enTenTen2020 corpus was consulted. In the second part of the paper, we analyze and compare the presentation of Coronavirus terminology in the descriptive Glossary of Coronavirus and the normative Croatian Web Dictionary – Mrežnik.
Within the scope of the project "Study and dissemination of COVID-19 terminology", the study reported here aims to detect, analyse and discuss the characteristics of COVID-19 terminology, in particular the role of the adjective novo [new] in this terminology, the high recurrence of terms in the plural and the resemantization of some of the terminological units used. The present paper also discusses how these characteristics influenced the choices that have guided the creation of the proposed dictionary. This paper presents, therefore, the results of the analyses of these aspects, starting with a discussion of the relation between terminology and neology and arriving at the characteristic aspects of the macrostructural and microstructural choices about which some considerations were made.