Young Adult Unemployment Through the Lens of Social Media: Italy as a Case Study

Urbinati, Alessandra; Kalimeri, Kyriaki; Bonanomi, Andrea; Rosina, Alessandro; Cattuto, Ciro; Paolotti, Daniela

doi:10.1007/978-3-030-60975-7_28

Cited by 5 publications

(4 citation statements)

References 54 publications

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“…In light of the aforementioned potentials of our approach, is crucial to recognize and address the inherent limitations associated with the utilization of non-traditional data sources [42], as LinkedIn advertising estimates. Especially when dealing with vulnerable populations digital data may reveal sensitive demographic patterns [6].…”

Section: Limitationsmentioning

confidence: 99%

From Ukraine to the World: Using LinkedIn Data to Monitor Professional Migration from Ukraine

Margherita

Paolotti

Kalimeri

2023

Proceedings of the 2023 ACM Conference on Information Technology for Social Good

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Highly skilled professionals' forced migration from Ukraine was triggered by the conflict in Ukraine in 2014 and amplified by the Russian invasion in 2022. Here, we utilize LinkedIn estimates and official refugee data from the World Bank and the United Nations Refugee Agency, to understand which are the main pull factors that drive the decision-making process of the host country. We identify an ongoing and escalating exodus of educated individuals, largely drawn to Poland and Germany, and underscore the crucial role of pre-existing networks in shaping these migration flows. Key findings include a strong correlation between LinkedIn's estimates of highly educated Ukrainian displaced people and official UN refugee statistics, pointing to the significance of prior relationships with Ukraine in determining migration destinations. We train a series of multilinear regression models and the SHAP method revealing that the existence of a support network is the most critical factor in choosing a destination country, while distance is less important. Our main findings show that the migration patterns of Ukraine's highly skilled workforce, and their impact on both the origin and host countries, are largely influenced by pre-existing networks and communities. This insight can inform strategies to tackle the economic challenges posed by this loss of talent and maximize the benefits of such migration for both Ukraine and the receiving nations.

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Section: Limitationsmentioning

confidence: 99%

From Ukraine to the World: Using LinkedIn Data to Monitor Professional Migration from Ukraine

Margherita

Paolotti

Kalimeri

2023

Proceedings of the 2023 ACM Conference on Information Technology for Social Good

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“…We used existing data previously collected via the LikeYouth Facebook-hosted application (https://likeyouth.org). LikeYouth is an innovative surveying tool originally conceived and developed independently by researchers at the ISI Foundation in Turin, Italy, where the second author is based, to address different research questions from the analyses reported here [48,70]. It was deployed in March 2016 mainly in Italy, where approximately 64,000 people entered the application.…”

Section: Datamentioning

confidence: 99%

Soundscapes of morality: Linking music preferences and moral values through lyrics and audio

Preniqi,

Kalimeri,

Saitis

2023

PLoS ONE

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Music is a fundamental element in every culture, serving as a universal means of expressing our emotions, feelings, and beliefs. This work investigates the link between our moral values and musical choices through lyrics and audio analyses. We align the psychometric scores of 1,480 participants to acoustics and lyrics features obtained from the top 5 songs of their preferred music artists from Facebook Page Likes. We employ a variety of lyric text processing techniques, including lexicon-based approaches and BERT-based embeddings, to identify each song’s narrative, moral valence, attitude, and emotions. In addition, we extract both low- and high-level audio features to comprehend the encoded information in participants’ musical choices and improve the moral inferences. We propose a Machine Learning approach and assess the predictive power of lyrical and acoustic features separately and in a multimodal framework for predicting moral values. Results indicate that lyrics and audio features from the artists people like inform us about their morality. Though the most predictive features vary per moral value, the models that utilised a combination of lyrics and audio characteristics were the most successful in predicting moral values, outperforming the models that only used basic features such as user demographics, the popularity of the artists, and the number of likes per user. Audio features boosted the accuracy in the prediction of empathy and equality compared to textual features, while the opposite happened for hierarchy and tradition, where higher prediction scores were driven by lyrical features. This demonstrates the importance of both lyrics and audio features in capturing moral values. The insights gained from our study have a broad range of potential uses, including customising the music experience to meet individual needs, music rehabilitation, or even effective communication campaign crafting.

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“…They also studied how social media data can complement studies about eating disorder [8], depression [2,36], personality traits [16] and general people characteristics [19]. Closer to the NEET case, recently Facebook data has been used to get a better understanding of Italian NEETs by tracking their digital behavior and comparing it with employed people [37]. Other works highlighted the importance of online communities for the NEETs, as they help them to stay connected while struggling with problems related to mental health and social anxiety [21,38].…”

Section: Social Media and Vulnerable Groupsmentioning

confidence: 99%

Complementing Studies on Vulnerable Youths with Reddit Data

Mauri¹,

Psyllidis

Bozzon

et al. 2021

CHItaly 2021: 14th Biannual Conference of the Italian SIGCHI Chapter

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Social web data increasingly complement studies of various social phenomena, especially when the availability of traditional data is limited. One such case is that of vulnerable young populations that are disengaged from employment, education, or training; usually referred to as NEETs. This paper explores the extent to which social media data and discussion websites could complement conventional sources in the study of NEETs. We focus on user-generated content posted to the dedicated r/NEET subreddit, which gathers subscribers who self-identify as NEETs. We develop and implement a data processing pipeline for the analysis of the behavioral patterns and main concerns of this social group. Our analysis of Reddit data reaches similar conclusions to official reports from governmental institutions in Europe. The paper also provides insights into healthrelated issues and latent interests of NEETs, not recorded in official reports and related literature. CCS CONCEPTS• Human-centered computing → Ethnographic studies; • Information systems → Social networks.

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Young Adult Unemployment Through the Lens of Social Media: Italy as a Case Study

Cited by 5 publications

References 54 publications

From Ukraine to the World: Using LinkedIn Data to Monitor Professional Migration from Ukraine

From Ukraine to the World: Using LinkedIn Data to Monitor Professional Migration from Ukraine

Soundscapes of morality: Linking music preferences and moral values through lyrics and audio

Complementing Studies on Vulnerable Youths with Reddit Data

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