This article presents the findings of a corpus linguistic analysis of the hashtags #mansplaining, #manspreading, and #manterruption, three lexical blends which have recently found widespread use across a variety of online media platforms. Focusing on the social media and microblogging site Twitter, we analyze a corpus of over 20,000 tweets containing these hashtags to examine how discourses of gender politics and gender relations are represented on the site. More specifically, our analysis suggests that users include these hashtags in tweets to index their individual evaluations of, and assumptions about, “proper” gendered behavior. Consequently, their metadiscursive references to the respective phenomena reflect their beliefs of what constitutes appropriate (verbal) behavior and the extent to which gender is appropriated as a variable dictating this behavior. As such, this article adds to our knowledge of the ways in which gendered social practices become sites of contestation and how contemporary gender politics play out in social media sites.
This chapter studies the form oops and its function as an Illocutionary Force Indicating Device (IFID) signalling apologies in a corpus of blog posts and reader comments. The focus is on the adaptability of speech acts to online media and the implications for the formal choice of linguistic expressions beyond the prototypical examples of routinised apology IFIDs. Thus, this study takes a closer look at the pragmatic functions of oops in the Birmingham Blog Corpus, a diachronically-structured collection covering the period 2000-2010, to gain new insights into its use and distribution.
This study addresses a familiar challenge in corpus pragmatic research: the search for functional phenomena in large electronic corpora. Speech acts are one area of research that falls into this functional domain and the question of how to identify them in corpora has occupied researchers over the past 20 years. This study focuses on apologies as a speech act that is characterised by a standard set of routine expressions, making it easier to search for with corpus linguistic tools. Nevertheless, even for a comparatively formulaic speech act, such as apologies, the polysemous nature of forms (cf. e.g. I am sorry vs. a sorry state) impacts the precision of the search output so that previous studies of smaller data samples had to resort to manual microanalysis. In this study, we introduce an innovative methodological approach that demonstrates how the combination of different types of collocational analysis can facilitate the study of speech acts in larger corpora. By first establishing a collocational profile for each of the Illocutionary Force Indicating Devices associated with apologies and then scrutinising their shared and unique collocates, unwanted hits can be discarded and the amount of manual intervention reduced. Thus, this article introduces new possibilities in the field of corpus-based speech act analysis and encourages the study of pragmatic phenomena in large corpora.
In computer-mediated communication, the medium of blogs is typically viewed as consisting of posts composed by blog authors and comments which may be left by their readers. This study explores the relationship between these constituent parts of blogs and investigates the pragmatic ties that are established between blog posts and comments. The focus is on the preface position in comments, that is the very first position at the onset of a comment, to discover how they are generally introduced and which specific linguistic constructions are used to initiate them. The aim is to uncover how speaker changesfrom blog author to commenter are signalled linguistically, in addition to the blog specific metadata provided by the interface (e.g. the username or time stamp), and which pragmatic means are used to develop interpersonal relationships between users. Results show that the preface position of blog comments is fertile ground for the occurrence of expressive speech acts with commenters often initiating their comments by thanking or complimenting blog authors, which opens up further opportunity for the study of speech acts in large corpora.
Despite the great strides made over the past thirty years by female comedy performers, their status in a male-dominated industry has typically been marginal. This is coupled with the widespread view that even women who do appear on mainstream comedy face the challenge of getting their voices heard in an arena where it is often the loudest voice that wins. In order to investigate claims that female comedians contribute less than male comedians on comedy panel shows, this article presents the findings of a sociolinguistic analysis of the British show Mock the Week, drawing on an XML-annotated corpus of the transcripts of series five. Rather than viewing features such as talkativeness and interruption solely as a substantiation of conversational dominance (cf. Brand 2009), we suggest that these could also be understood as strategies in the production of humour in the context of comedy panel shows. In addition to genre-specific considerations, our results show that the use of these features on Mock theWeek is influenced by an interplay of social factors, rather than gender alone. Overall, this study could act as a catalyst for writers and production companies to use more linguisticallyinformed approaches to comedy show scripting, particularly in relation to issues of linguistic and representational inequality.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.