A text mining analysis of human flourishing on Twitter

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A93DPFQZW" target="_blank" >RIV/00216208:11320/23:93DPFQZW - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149153525&doi=10.1038%2fs41598-023-30209-7&partnerID=40&md5=8fc9655f03c53b06c7655264289f9c9e" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149153525&doi=10.1038%2fs41598-023-30209-7&partnerID=40&md5=8fc9655f03c53b06c7655264289f9c9e</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-023-30209-7" target="_blank" >10.1038/s41598-023-30209-7</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A text mining analysis of human flourishing on Twitter

Popis výsledku v původním jazyce

"The power of social media in spreading the idea of wellbeing has already been addressed by several psychologists and scholars through the analysis of the vocabulary; however, the use of the human flourishing (HF) concept in such platforms has not yet been analyzed. This study addresses such a topic by analyzing more than 600 thousand Twitter messages posted by a community of users who associate themselves with HF and comparing them to more than 400 thousand messages in other Twitter lists. The study aims to identify the HF users’ interests, the richness in their vocabulary, the feelings and emotions that they share, and the grammar used in their constructions. Such an analysis was conducted through text mining computational methods, including sentiment analysis, natural language processing (NLP), and topic modeling. The results revealed that although HF users employ average vocabulary diversity, they share more positive emotions, and a greater variety of emojis. They also tended to discuss different topics, from more spiritual and health-related subjects to more practical matters related to work and success. Finally, they generally wrote from an empathetic state of mind, caring about people’s day-to-day feelings and about the world. © 2023, The Author(s)."

Název v anglickém jazyce

A text mining analysis of human flourishing on Twitter

Popis výsledku anglicky

"The power of social media in spreading the idea of wellbeing has already been addressed by several psychologists and scholars through the analysis of the vocabulary; however, the use of the human flourishing (HF) concept in such platforms has not yet been analyzed. This study addresses such a topic by analyzing more than 600 thousand Twitter messages posted by a community of users who associate themselves with HF and comparing them to more than 400 thousand messages in other Twitter lists. The study aims to identify the HF users’ interests, the richness in their vocabulary, the feelings and emotions that they share, and the grammar used in their constructions. Such an analysis was conducted through text mining computational methods, including sentiment analysis, natural language processing (NLP), and topic modeling. The results revealed that although HF users employ average vocabulary diversity, they share more positive emotions, and a greater variety of emojis. They also tended to discuss different topics, from more spiritual and health-related subjects to more practical matters related to work and success. Finally, they generally wrote from an empathetic state of mind, caring about people’s day-to-day feelings and about the world. © 2023, The Author(s)."

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

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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

2023

Kód důvěrnosti údajů

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

Název periodika

"Scientific Reports"

ISSN

2045-2322

e-ISSN

—

Svazek periodika

13

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

12

Strana od-do

1-12

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85149153525