The covid-19 crisis: An nlp exploration of the french twitter feed (february-may 2020)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10441772" target="_blank" >RIV/00216208:11320/21:10441772 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-77685-5_24" target="_blank" >https://doi.org/10.1007/978-3-030-77685-5_24</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-77685-5_24" target="_blank" >10.1007/978-3-030-77685-5_24</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The covid-19 crisis: An nlp exploration of the french twitter feed (february-may 2020)

Popis výsledku v původním jazyce

The Covid-19 pandemic offers a spectacular case of disaster management. In this literature, the paradigm of participation is fundamental: the mitigation of the impact of the disaster, the quality of the preparation and the resilience of the society, which facilitate the reconstruction, depend on the participation of the populations. Being able to observe and measure the state of mental health of the population (anx-iety, confidence, expectations, ...) and to identify the points of controversy and the content of the discourse, are necessary to support measures designed to encourage this participation. Social media, and in particular Twitter, offer valuable resources for researching this discourse. The objective of this empirical study is to reconstruct a micro history of users&apos; reactions to the pandemic as they share them on social networks. The general method used comes from new processing techniques derived from Natural Language Processing (NLP). Three analysis methods are used to process the corpus: analysis of the temporal evolution of term occurrences; creation of dynamic semantic maps to identify co-occurrences; analysis of topics using the SVM method. The main empirical result is that the mask emerges as a central figure of discourse, at least in the discourse produced by certain social media. The retrospective analysis of the phenomenon allows us to explain what made the mask a focal point not only in conversation, but also in behaviors. Its value resides less in its functional qualities than in its ability to fix attention and organize living conditions under the threat of pandemic.

Název v anglickém jazyce

The covid-19 crisis: An nlp exploration of the french twitter feed (february-may 2020)

Popis výsledku anglicky

The Covid-19 pandemic offers a spectacular case of disaster management. In this literature, the paradigm of participation is fundamental: the mitigation of the impact of the disaster, the quality of the preparation and the resilience of the society, which facilitate the reconstruction, depend on the participation of the populations. Being able to observe and measure the state of mental health of the population (anx-iety, confidence, expectations, ...) and to identify the points of controversy and the content of the discourse, are necessary to support measures designed to encourage this participation. Social media, and in particular Twitter, offer valuable resources for researching this discourse. The objective of this empirical study is to reconstruct a micro history of users&apos; reactions to the pandemic as they share them on social networks. The general method used comes from new processing techniques derived from Natural Language Processing (NLP). Three analysis methods are used to process the corpus: analysis of the temporal evolution of term occurrences; creation of dynamic semantic maps to identify co-occurrences; analysis of topics using the SVM method. The main empirical result is that the mask emerges as a central figure of discourse, at least in the discourse produced by certain social media. The retrospective analysis of the phenomenon allows us to explain what made the mask a focal point not only in conversation, but also in behaviors. Its value resides less in its functional qualities than in its ability to fix attention and organize living conditions under the threat of pandemic.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISBN

978-3-030-77684-8

ISSN

—

e-ISSN

—

Počet stran výsledku

14

Strana od-do

308-321

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

online

Datum konání akce

24. 7. 2021

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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