#Bieber + #Blast = #BieberBlast

Maity, Suman Kalyan; Saraf, R.K.; Mukherjee, Animesh

doi:10.1145/2818048.2820019

Cited by 7 publications

(11 citation statements)

References 42 publications

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“…Diffusion of information and cultural items. As discussed in the introduction, there has been a long line of work studying the processes by which discrete units of information diffuse on-line; these include memes [28,31], hashtags on Twitter [36,37,29] and on-line news content [1,7,5]. A growing strand of research within this topic has considered the problem of predicting future popularity, with specific prediction studies involving downloadable content [39], quotes embedded in broader cultural contexts [11,6], hashtags [42], and memes [9,43].…”

Section: Further Related Workmentioning

confidence: 99%

Competition and Selection Among Conventions

Rotabi

Danescu-Niculescu-Mizil

Kleinberg

2017

Proceedings of the 26th International Conference on World Wide Web

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In many domains, a latent competition among different conventions determines which one will come to dominate. One sees such effects in the success of community jargon, of competing frames in political rhetoric, or of terminology in technical contexts. These effects have become widespread in the on-line domain, where the ease of information transmission makes them particularly forceful, and where the available data offers the potential to study competition among conventions at a fine-grained level.In analyzing the dynamics of conventions over time, however, even with detailed on-line data, one encounters two significant challenges. First, as conventions evolve, the underlying substance of their meaning tends to change as well; and such substantive changes confound investigations of social effects. Second, the selection of a convention takes place through the complex interactions of individuals within a community, and contention between the users of competing conventions plays a key role in the convention's evolution. Any analysis of the overall dynamics must take place in the presence of these two issues.In this work we study a setting in which we can cleanly track the competition among conventions while explicitly taking these sources of complexity into account. Our analysis is based on the spread of low-level authoring conventions in the e-print arXiv over 24 years and roughly a million posted papers: by tracking the spread of macros and other author-defined conventions, we are able to study conventions that vary even as the underlying meaning remains constant. We find that the interaction among co-authors over time plays a crucial role in the selection of conventions; the distinction between more and less experienced members of the community, and the distinction between conventions with visible versus invisible effects, are both central to the underlying processes. Through our analysis we make predictions at the population level about the ultimate success of different synonymous conventions over time -and at the individual level about the outcome of "fights" between people over convention choices.

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Section: Further Related Workmentioning

confidence: 99%

Competition and Selection Among Conventions

Rotabi

Danescu-Niculescu-Mizil

Kleinberg

2017

Proceedings of the 26th International Conference on World Wide Web

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“…Other hashtags have a cyclic life-span, whereby they are only used in specific months of the year recurrently, and not in other months (e.g., #TreatyofWaitangi). In general, as also noted by Maity et al (2016), hashtags are highly transient and their life-span tends to be short. The hybrid hashtags in the HH sub-corpus are no exception to this trend.…”

Section: Measuring Hashtag Survival/life-spanmentioning

confidence: 81%

“…As mentioned in section 2, there is divided opinion in the literature regarding the morphological word-formation process which gives rise to hashtags (see especially Caleffi, 2015;Maity et al, 2016). The most intuitive way to classify the formation of hashtags is by recourse to compounding, which is a problematic process in itself (see discussion in Bauer, 2017), but which appears to be among the most productive mechanism for creating new words in English.…”

Section: Word-formation In Hybrid Hashtagsmentioning

confidence: 99%

Hybrid Hashtags: #YouKnowYoureAKiwiWhen Your Tweet Contains Māori and English

Trye

Calude

Bravo-Márquez

et al. 2020

Front. Artif. Intell.

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Twitter constitutes a rich resource for investigating language contact phenomena. In this paper, we report findings from the analysis of a large-scale diachronic corpus of over one million tweets, containing loanwords from te reo Māori, the indigenous language spoken in New Zealand, into (primarily, New Zealand) English. Our analysis focuses on hashtags comprising mixed-language resources (which we term hybrid hashtags), bringing together descriptive linguistic tools (investigating length, word class, and semantic domains of the hashtags) and quantitative methods (Random Forests and regression analysis). Our work has implications for language change and the study of loanwords (we argue that hybrid hashtags can be linked to loanword entrenchment), and for the study of language on social media (we challenge proposals of hashtags as "words," and show that hashtags have a dual discourse role: a micro-function within the immediate linguistic context in which they occur and a macro-function within the tweet as a whole).

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“…Coupled with timelines and historical dates, the life and death of a hashtag can also be analyzed as related to the impact of the event or movement diachronically. (For more on the life and death of hashtags, see Cunha et al 2011; Glasgow & Fink, 2013; Maity, Saraf, & Mukherjee, 2016; Varol, Ferrara, Ogan, Menczer, & Flammini, 2014). Examples of this pattern can be found in the analysis of the hashtags used during the London riots (Glasgow & Fink, 2013), the 2012 U.S. presidential debates (Lin, Margolin, Keegan, Baronchelli, & Lazer, 2013), and the 2012 Mexican presidential election (Abascal-Mena, López-Ornelas, & Zepeda-Hernández, 2013).…”

Section: Hashtagsmentioning

confidence: 99%

Emergent Digital Discourses: What Can We Learn From Hashtags and Digital Games to Expand Learners’ Second Language Repertoire?

Sykes

2019

Ann Rev Appl Linguist

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In recent years, digital technologies have expanded the possibilities for human interactions in ways that were never before imagined, further complicating the teaching and learning of languages (Taguchi & Sykes, 2013; Thorne, Sauro, & Smith, 2015). Despite this complexity, when approached as meaningful, high-stakes practices, discourses in digital contexts can be highly useful for language learning and teaching. This article synthesizes work related to two digital discourse contexts, specifically hashtags and digital games. Moving away from technology as the vehicle to deliver “important content,” the analysis to follow examines digital discourses as both the content and context to be examined as part of learners’ multilingual experiences. The article begins by situating the discussion focused on digital discourses, reviewing relevant work addressing interactional patterns in each context, and then applying findings to second language teaching and learning. Drawing on empirical work, the article then describes a framework with specific examples for learner exploration of digital discourses as part of their language learning experience. The article concludes with implications for future research and teaching.

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#Bieber + #Blast = #BieberBlast

Cited by 7 publications

References 42 publications

Competition and Selection Among Conventions

Competition and Selection Among Conventions

Hybrid Hashtags: #YouKnowYoureAKiwiWhen Your Tweet Contains Māori and English

Emergent Digital Discourses: What Can We Learn From Hashtags and Digital Games to Expand Learners’ Second Language Repertoire?

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