The present study examines language used to talk about the global coronavirus pandemic during a three-month period of movement control order in Malaysia. More specifically, a corpus of online letters to the editor of a local popular national newspaper was collected during the time in which the official quarantine instruction was initiated, resulting in a total of 303 online letters written by Malaysians that were analyzed through use of corpus linguistics techniques. For this purpose, the latest version of #LancsBox 5.0 (Brezina et al., 2020) is used to analyze patterns of language surrounding the portrayal of Covid-19 and further visualizing them by use of collocation networks. Findings present 25 statistically significant collocates that share an interesting relationship in revealing what the letters are about and thus, reflecting how Malaysians perceive and receive news about the pandemic during this time. Recurring topics and expressions include describing the virus in terms of metaphorical use of language (Covid-19 does not discriminate), preparing for an economic fallout (Prihatin Economic Stimulus Package), and preference to associate Covid-19 as a pandemic (impacts of the Covid19 pandemic) rather than an outbreak (first/second/third wave of the outbreak). Implications of the study resonates with findings from Azizan et al. (2020) where constructions of positive discourse among Malaysian writers may reflect the culture and society that make up the nation.

This paper investigates changes in relativization in Singapore English broadsheet newspapers from 1993 to 2016. One of the first diachronic studies in Singapore English (SgE), it also explores corresponding data from the diachronic Siena-Bologna (SiBol) news corpus. As SgE is in the endonormative stabilization phase in Schneider's (2007) Dynamic Model of postcolonial Englishes, divergence from British English (BrE) is to be expected. In this study, the dataset is a new Singapore English Newspaper (SEN) corpus compiled from local news articles in 1993, 2005 and 2016, and the corpus tool employed is Sketch Engine. The results reveal changes in relativization practices in SEN over the given period, many of which occur in a similar pattern as those identified in SiBol, albeit at varying rates of change. Most significant of these include a sharp decline in the which relativizer in restrictive relative clauses with non-animate antecedents, complemented by a rise in that. The change has been so rapid that although which relative clauses were more common than that clauses in 1993, that has subsequently overtaken which for both the corpora. One shift in SEN that is different from SiBol is the increase in frequency of non-restrictive relative clauses in SgE. The likely motivators for the changes in the two varieties are identified as colloquialization, densification and prescriptivism. The effect each of these factors could have had on the varieties are discussed, as well as the implications that the findings have on our understanding of the evolutionary status of SgE as a postcolonial variety.

The present study examined vocabulary usage in elementary English classrooms in Japan using elementary school corpus. The authors used three wordlists to benchmark the lexical items for four classes in the corpus: the CEFR-J, the General Service List (GSL), and Academic Word List (AWL). The percentage of vocabulary usage belonging to the Level A1 in the CEFR-J was below 15% (Class A: 12.1%, Class B: 12.6%, Class C: 8.9%, and Class D: 13.6%) with no statistical difference between levels. The mean ratio of Level A2 vocabulary items was below 10%, and all classes showed less than 1% of vocabulary usage for the Levels B1 and B2. Over 70% of all vocabulary items in the corpus belonged to the most frequent 1,000-word band (level 1) of the GSL, while the next most frequent word band (level 2 of the GSL and AWL) accounted for less than 10%. The results suggest that elementary school English teachers should use more vocabulary items in the CEFR-J Level A1. The findings demonstrate that elementary school teachers are less likely to expose their pupils to grammatically well-structured sentences with an abundance of lexical items since the teachers repeatedly use the same lexemes in each class.

This paper aims to inform people how to support each other on social media. It alludes to an architecture for social media discourse and proposes a novel theory of support in social media discourse. It makes a methodological contribution. It combines predominately artificial intelligence with corpus linguistics analysis. It is on a large-scale dataset of anonymised diabetes-related user's posts from the Facebook platform. Log-likelihood and precision measures help with validation. A multi-method approach with Discourse Analysis helps in understanding any potential patterns. People living with Diabetes are found to employ sophisticated high-frequency patterns of device-enabled categories of purpose and content. It is with, for example, linguistic forms of Advice with stance-taking and targets such as Diabetes amongst other interactional ways. There can be uncertainty and variation of effect displayed when sharing information for support. The implications of the new theory aim at healthcare communicators, corpus linguists and with preliminary work for AI support-bots. These bots may be programmed to utilise the language patterns to support people who need them automatically.

The purpose of this review is to provide local readers, more specifically, Korean student readers who are not all that familiar with the English language a general overview of research articles that have been published in Asia Pacific Journal of Corpus Research vol. 1, no. 1. A brief summary of each research article focusing on research methods and then followed by an overall review and some insights on research issues will be presented.