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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-09252024-214654


Tipo di tesi
Tesi di laurea magistrale
Autore
CEKINI, KAMER
Indirizzo email
k.cekini@studenti.unipi.it, kamer.cekini1@gmail.com
URN
etd-09252024-214654
Titolo
COVID-19's Impact on Twitter Ego Networks
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Prof.ssa Ricci, Laura Emilia Maria
relatore Dott. Passarella, Andrea
relatore Dott.ssa Boldrini, Chiara
relatore Dott.ssa Biondi, Elisabetta
Parole chiave
  • Covid
  • Data Science
  • Ego network
  • Lockdown
  • Signed ego network
  • Twitter
  • X
Data inizio appello
11/10/2024
Consultabilità
Non consultabile
Data di rilascio
11/10/2094
Riassunto
One of the most impactful measures to fight the COVID19 pandemic in its early first years was the lockdown, implemented by governments to reduce physical contact among people and minimize opportunities for the virus to spread. As people were compelled to limit their physical interactions and stay at home, they turned to online social platforms to alleviate feelings of loneliness. Ego networks represent how people organize their relationships due to human cognitive constraints that impose limits on meaningful interactions among people. Physical contacts were disrupted during the lockdown, causing socialization to shift entirely online, leading to a shift in socialization into online plat forms. Our research aimed to investigate the impact of lockdown measures on online ego network structures potentially caused by the increase of cognitive expenses in online social networks. In particular, we examined a large Twitter dataset of users, covering 7 years of their activities. We found that during the lockdown, there was an increase in network sizes and a richer structure in social circles, with relationships becoming more intimate. Moreover, we observe that, after the lockdown measures were relaxed, these features returned to their pre-lockdown values.
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