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Computer Science > Social and Information Networks

arXiv:2204.10646 (cs)
[Submitted on 22 Apr 2022]

Title:Measuring the Salad Bowl: Superdiversity on Twitter

Authors:Laura Pollacci, Alina Sirbu, Fosca Giannotti, Dino Pedreschi
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Abstract:Superdiversity refers to large cultural diversity in a population due to immigration. In this paper, we introduce a superdiversity index based on the changes in the emotional content of words used by a multi-cultural community, compared to the standard language. To compute our index we use Twitter data and we develop an algorithm to extend a dictionary for lexicon-based sentiment analysis. We validate our index by comparing it with official immigration statistics available from the European Commission's Joint Research Center, through the D4I data challenge. We show that, in general, our measure correlates with immigration rates, at various geographical resolutions. Our method produces very good results across languages, being tested here both on English and Italian tweets. We argue that our index has predictive power in regions where exact data on immigration is not available, paving the way for a nowcasting model of immigration rates.
Subjects: Social and Information Networks (cs.SI)
Cite as: arXiv:2204.10646 [cs.SI]
  (or arXiv:2204.10646v1 [cs.SI] for this version)
  https://doi.org/10.48550/arXiv.2204.10646

Submission history

From: Laura Pollacci [view email]
[v1] Fri, 22 Apr 2022 11:30:58 UTC (2,140 KB)
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