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Sociolinguistic analysis of Twitter in multilingual societies

Published: 01 September 2014 Publication History

Abstract

In a multilingual society, language not only reflects culture and heritage, but also has implications for social status and the degree of integration in society. Different languages can be a barrier between monolingual communities, and the dynamics of language choice could explain the prosperity or demise of local languages in an international setting. We study this interplay of language and network structure in diverse, multi-lingual societies, using Twitter. In our analysis, we are particularly interested in the role of bilinguals. Concretely, we attempt to quantify the degree to which users are the "bridge-builders" between monolingual language groups, while monolingual users cluster together. Also, with the revalidation of English as a lingua franca on Twitter, we reveal users of the native non-English language have higher influence than English users, and the language convergence pattern is consistent across the regions. Furthermore, we explore for which topics these users prefer their native language rather than English. To the best of our knowledge, this is the largest sociolinguistic study in a network setting.

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    cover image ACM Conferences
    HT '14: Proceedings of the 25th ACM conference on Hypertext and social media
    September 2014
    346 pages
    ISBN:9781450329545
    DOI:10.1145/2631775
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 01 September 2014

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    Author Tags

    1. multilingualism
    2. social media
    3. sociolinguistics
    4. topic modeling

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    Overall Acceptance Rate 378 of 1,158 submissions, 33%

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    • (2024)Large scale annotated dataset for code-mix abusive short noisy textLanguage Resources and Evaluation10.1007/s10579-023-09707-7Online publication date: 25-Jan-2024
    • (2023)You Can (Not) Say What You Want: Using Algospeak to Contest and Evade Algorithmic Content Moderation on TikTokSocial Media + Society10.1177/205630512311945869:3Online publication date: 31-Aug-2023
    • (2023)A systems approach to multilingual language attitudes: A case study of Montréal, Québec, CanadaInternational Journal of Bilingualism10.1177/1367006922113330528:3(454-478)Online publication date: 25-Apr-2023
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