Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/90879
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Chinese and Bilingual Studies | en_US |
| dc.contributor | Department of English | en_US |
| dc.creator | Jiang, M | en_US |
| dc.creator | Shen, XY | en_US |
| dc.creator | Ahrens, K | en_US |
| dc.creator | Huang, CR | en_US |
| dc.date.accessioned | 2021-09-03T02:34:48Z | - |
| dc.date.available | 2021-09-03T02:34:48Z | - |
| dc.identifier.uri | http://hdl.handle.net/10397/90879 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Public Library of Science | en_US |
| dc.rights | © 2021 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | en_US |
| dc.rights | The following publication Jiang M, Shen XY, Ahrens K, Huang C-R (2021) Neologisms are epidemic: Modeling the life cycle of neologisms in China 2008-2016. PLoS ONE 16(2): e0245984 is available at https://doi.org/10.1371/journal.pone.0245984 | en_US |
| dc.title | Neologisms are epidemic : modeling the life cycle of neologisms in China 2008-2016 | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.volume | 16 | en_US |
| dc.identifier.issue | 2 | en_US |
| dc.identifier.doi | 10.1371/journal.pone.0245984 | en_US |
| dcterms.abstract | This paper adopts models from epidemiology to account for the development and decline of neologisms based on internet usage. The research design focuses on the issue of whether a host-driven epidemic model is well-suited to explain human behavior regarding neologisms. We extracted the search frequency data from Google Trends that covers the ninety most influential Chinese neologisms from 2008-2016 and found that the majority of them possess a similar rapidly rising-decaying pattern. The epidemic model is utilized to fit the evolution of these internet-based neologisms. The epidemic model not only has good fitting performance to model the pattern of rapid growth, but also is able to predict the peak point in the neologism's life cycle. This result underlines the role of human agents in the life cycle of neologisms and supports the macro-Theory that the evolution of human languages mirrors the biological evolution of human beings. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | PLoS one, 3 Feb. 2021, v. 16, no. 2, e0245984 | en_US |
| dcterms.isPartOf | PLoS one | en_US |
| dcterms.issued | 2021-02 | - |
| dc.identifier.scopus | 2-s2.0-85100667309 | - |
| dc.identifier.pmid | 33534795 | - |
| dc.identifier.eissn | 1932-6203 | en_US |
| dc.identifier.artn | e0245984 | en_US |
| dc.description.validate | 202109 bcvc | en_US |
| dc.description.oa | Version of Record | en_US |
| dc.identifier.FolderNumber | OA_Scopus/WOS, a3532a | - |
| dc.identifier.SubFormID | 50306 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | Marie Sklodowska-Curie Innovative Training Network project titled “Conversational Brains: A Multidisciplinary Approach” (grant agreement n˚859588); Hong Kong Polytechnic University (#ZG9X); Hong Kong Polytechnic University and Peking University Joint Research Centre on Chinese Linguistics (RP2U2) | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | CC | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| journal.pone.0245984.pdf | 1.74 MB | Adobe PDF | View/Open |
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