In this study, we conducted a comprehensive data collection on the 2022 Qatar FIFA World Cup event and used a multilayer network approach to visualize the main topics, while considering their context and meaning relationships. We struc- tured the data into layers that corresponded with the stages of the tournament and utilized Gephi software to generate the multilayer networks. Our visualiza- tions displayed both the relationships between topics and words, showing the word-context relationship, as well as the dynamics and changes over time by layer of the most frequently discussed topics.
Topics evolution through multilayer networks; Analysing 2M tweets from 2022 Qatar FIFA World Cup
Andrea Russo
Primo
;Vincenzo MiraculaSecondo
;Antonio PiconeUltimo
2023-01-01
Abstract
In this study, we conducted a comprehensive data collection on the 2022 Qatar FIFA World Cup event and used a multilayer network approach to visualize the main topics, while considering their context and meaning relationships. We struc- tured the data into layers that corresponded with the stages of the tournament and utilized Gephi software to generate the multilayer networks. Our visualiza- tions displayed both the relationships between topics and words, showing the word-context relationship, as well as the dynamics and changes over time by layer of the most frequently discussed topics.File in questo prodotto:
| File | Dimensione | Formato | |
|---|---|---|---|
|
Russo_bookOfAbstractsFRCCS2023.pdf
accesso aperto
Tipologia:
Versione Editoriale (PDF)
Licenza:
Creative commons
Dimensione
6.62 MB
Formato
Adobe PDF
|
6.62 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


