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Where do migrants and natives belong in a community: a Twitter case study and privacy risk analysis

Academic Article
Publication Date:
2022
abstract:
Today, many users are actively using Twitter to express their opinions and to share information. Thanks to the availability of the data, researchers have studied behaviours and social networks of these users. International migration studies have also benefited from this social media platform to improve migration statistics. Although diverse types of social networks have been studied so far on Twitter, social networks of migrants and natives have not been studied before. This paper aims to fill this gap by studying characteristics and behaviours of migrants and natives on Twitter. To do so, we perform a general assessment of features including profiles and tweets, and an extensive network analysis on the network. We find that migrants have more followers than friends. They have also tweeted more despite that both of the groups have similar account ages. More interestingly, the assortativity scores showed that users tend to connect based on nationality more than country of residence, and this is more the case for migrants than natives. Furthermore, both natives and migrants tend to connect mostly with natives. The homophilic behaviours of users are also well reflected in the communities that we detected. Our additional privacy risk analysis showed that Twitter data can be safely used without exposing sensitive information of the users, and minimise risk of re-identification, while respecting GDPR.
Iris type:
01.01 Articolo in rivista
Keywords:
International migration; Community detection; Social network; Twitter; Privacy risk assessment; GDPR
List of contributors:
Rossetti, Giulio; Pratesi, Francesca
Authors of the University:
PRATESI FRANCESCA
ROSSETTI GIULIO
Handle:
https://iris.cnr.it/handle/20.500.14243/418660
Full Text:
https://iris.cnr.it//retrieve/handle/20.500.14243/418660/113009/prod_475957-doc_194475.pdf
Published in:
SOCIAL NETWORK ANALYSIS AND MINING
Journal
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URL

https://link.springer.com/article/10.1007/s13278-022-01017-0
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