27. Code-switching in computer-mediated communication

Androutsopoulos, Jannis

doi:10.1515/9783110214468.667

Cited by 141 publications

(76 citation statements)

References 16 publications

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“…Language choice is generally a broad conception concerning codes or linguistic recourses available to online participants. CS is defined as "dialogically interrelated by responding to previous, and contextualizing subsequent, contributions" [10]. Therefore, CS is more closely related with the online writing interactions (mainly Comments) [8].…”

Section: B Multilingual Writing Practices Onlinementioning

confidence: 99%

“…Studies on online CS are well documented in [10] and [8], including different chosen platforms, languages, participants, methods and themes. Moreover, the structural patterns (insertional, alternational, intraword CS) and motivations of CS have also been comprehensively and succinctly summarized in [10] and [8].…”

Section: B Multilingual Writing Practices Onlinementioning

confidence: 99%

“…Moreover, the structural patterns (insertional, alternational, intraword CS) and motivations of CS have also been comprehensively and succinctly summarized in [10] and [8]. Studies conducted in different sociocultural backgrounds reveal different reasons for CS, such as language preference [11], cultural value, ethnic identities [12], [13], [14], site's affordances [15], economic concerns [3] and etc.…”

Section: B Multilingual Writing Practices Onlinementioning

confidence: 99%

“…The main tools for data collection are exploratory observation [4] and email interview [19]. Collected data consists of screen-based data (including profile, hashtag, caption and comments) and user-based data (mainly through instant messages on Instagram and email-interview) [10]. Most participants prefer to communicate in Chinese.…”

Section: Data Collection Processmentioning

confidence: 99%

See 3 more Smart Citations

Chinese or English? Writing Practices of Users from Mainland China on Instagram

Li¹

2017

IJLLL

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Section: B Multilingual Writing Practices Onlinementioning

confidence: 99%

Section: B Multilingual Writing Practices Onlinementioning

confidence: 99%

Section: B Multilingual Writing Practices Onlinementioning

confidence: 99%

Section: Data Collection Processmentioning

confidence: 99%

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Chinese or English? Writing Practices of Users from Mainland China on Instagram

Li¹

2017

IJLLL

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“…Over 10% of the Twitter users tweet in more than one language (Hale, 2014) and code-switching has been observed on various social media platforms as well (Androutsopoulos, 2013; Johnson, 2013; Jurgens et al, 2014; Nguyen et al, 2015). The occurrence of code-switching in online communication has sparked interest in two research directions.…”

Section: Introductionmentioning

confidence: 99%

Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology

Elsner¹,

Kuebler²

2016

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Welcome to the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology. The workshop aims to bring together researchers interested in applying computational techniques to problems in morphology, phonology, and phonetics. Our program this year highlights the ongoing and important interaction between work in computational linguistics and work in theoretical linguistics. We received 23 submissions and accepted 11.The volume of submissions made it necessary to recruit several additional reviewers. We'd like to thank all of these people for agreeing to review papers on what seemed like impossibly short notice.This year also marks the first SIGMORPHON shared task, on morphological reinflection. The shared task received 9 submissions, all of which were accepted, and greatly advanced the state of the art in this area.We thank all the authors, reviewers and organizers for their efforts on behalf of the community. AbstractThis paper conceptualizes speech prosody data mining and its potential application in data-driven phonology/phonetics research. We first conceptualize Speech Prosody Mining (SPM) in a time-series data mining framework. Specifically, we propose using efficient symbolic representations for speech prosody time-series similarity computation. We experiment with both symbolic and numeric representations and distance measures in a series of time-series classification and clustering experiments on a dataset of Mandarin tones. Evaluation results show that symbolic representation performs comparably with other representations at a reduced cost, which enables us to efficiently mine large speech prosody corpora while opening up to possibilities of using a wide range of algorithms that require discrete valued data. We discuss the potential of SPM using time-series mining techniques in future works. IntroductionCurrent investigations on the phonology of intonation and tones (or pitch accent) typically employ data-driven approaches by building research on top of manual annotations of a large amount of speech prosody data (for example, (Morén and Zsiga, 2006; Zsiga and Zec, 2013), and many others). Meanwhile, researchers are also limited by the amount of resources invested in such expensive endeavor of manual annotations. Given this paradox, we believe that this type of data driven approach in phonology-phonetics interface can benefit from tools that can efficiently index, query, classify, cluster, summarize, and discover meaningful prosodic patterns from a large speech prosody corpus.The data mining of f 0 1 (pitch) contour patterns from audio data has recently gained success in the domain of Music Information Retrieval (aka MIR, see (Gulati and Serra, 2014; Gulati et al., 2015; Ganguli, 2015) for examples). In contrast, the data mining of speech prosody f 0 data (here on referred to as Speech Prosody Mining (SPM) 2 ) is a less explored research topic (Raskinis and Kazlauskiene, 2013). Fundamentally, SPM in a large prosody corpus aims at discovering meaningful patterns in the f ...

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Contact and Code‐Switching

Gardner‐Chloros¹

2020

The Handbook of Language Contact

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Language contact has been invoked with increasing frequency over the past two or three decades as a, or the, cause of a wide range of linguistic changes. Historical linguists have (of course) mainly addressed these changes from a diachronic perspective -that is, analyzing ways in which language contact has influenced lexical and/or structural developments over time. But sociolinguists, and many or most of the scholars who would characterize their specialty as contact linguistics, have focused on processes involving contact in analyzing synchronic variation. A few scholars have even argued that contact is the sole source of lan guage variation and change; this extreme position is a neat counterpoint to an older position in historical linguistics, namely, that language contact is responsible only for lexical changes and quite minor structural changes. (This long-superseded older position is echoed, surpris ingly, in Labov's recent claim that 'structural borrowing is rare ' and superficial (Labov 2007: 349, 383).) In this chapter I will argue that neither extreme position is viable. This argument will be developed through a survey of general types of contact explanations, especially explanations for changes over time, juxtaposed with a comparative survey of major causal factors in internally-motivated language change. My goal is to show that both internal and external motivations are needed in any full account of language history (Hickey 2012) and, by implication, of synchronic variation. Progress in contact linguistics depends, in my opinion, on recognizing the complexity of change processes -on resisting the urge to offer a single simple explanation for all types of structural change.The structure of the chapter is as follows. Section 1 provides some background concepts and definitions, and sections 2 and 3 compare and contrast contact explanations with internal explanations of change. Section 4 discusses a much-cited typology-based theory about contact vs. internal explanations. Section 5, finally, is a brief conclusion that includes a warning about the need to be cautious in making claims about the causes of change -both because in most cases no cause can be firmly established and because of the real possibility that multiple causes are responsible for a particular change. Some Background ConceptsFirst, what counts as language contact? The mere juxtaposition of two speakers of different languages, or two texts in different languages, is too trivial to count: unless the speakers or the texts interact in some way, there can be no transfer of linguistic features in either direction. Only when there is some interaction does the possibility of a contact explanation for

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27. Code-switching in computer-mediated communication

Cited by 141 publications

References 16 publications

Chinese or English? Writing Practices of Users from Mainland China on Instagram

Chinese or English? Writing Practices of Users from Mainland China on Instagram

Proceedings of the 14th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology

Contact and Code‐Switching

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