[TMP-023] Building TRUST in social media: assessing the Trustworthiness of public Information on Ukrainian Migration to Europe

Contact person: Nina Khairova (nina.khairova@umu.se) 

Internal Partners:

1. Umea University, Nina Khairova, nina.khairova@umu.se

External Partners:

1. Gdansk University of Technology, Nina Rizun, nina.rizun@pg.edu.pl
2. University of the Aegean, Charalampos Alexopoulos, alexop@aegean.g   

Currently, almost all government, commercial, and non-profit organizations actively use social media for the dissemination of information and communication with citizens. Social media should serve to enhance citizen engagement and trust, contribute to the improvement of government institutions’ transparency, and guarantee freedom of speech and expression. However, the government needs to be aware of and mitigate the risks associated with the use of social media. One of the most significant is the risk of spreading misinformation that has become increasingly prevalent and easily accessible to the global social media audience.

In general, the government and public officials’ social media accounts are trustworthy and aim to disseminate high-quality and timely information to the public ensuring its reliability, integrity, accessibility, and validity. However, non-compliance with the rules of effective and trusted two-way communication on public officials’ accounts, untimely updating of the communication channel, and incomplete responses to user comments could lead to a tendency of citizens to search (or check) the information in other social media sources. Such information sources include traditional news outlets, professional or casual journalists, or ordinary users. Wherein the risk of misinformation being disseminated could undermine citizens’ trust in the government, as well as threaten the security and privacy of both official government data and personal data. Moreover, the sharing of inaccurate and misleading information could lead to significant social consequences, such as the exacerbation of social inequalities, the creation of social divisions between different social groups, and the manipulation of their opinions.

In our microproject, we strive to develop an actionable AI-based approach to objectively assess information trustworthiness on social media based on the combination of AI algorithms, such as unsupervised machine learning, text analytics, and event argument extraction. We apply our approach to the analysis of textual information in Polish, Ukrainian, and English thematically related to the main ethical, legal, and societal issues caused by the migration of Ukrainians to European countries as a result of the ongoing Russian invasion. The choice of migration crisis domain to assess the reliability of social media information is due to the following reasons. First, as recent research demonstrates, migration issues are among the most hotly debated on social media and can be especially subjected to attempts of various kinds of disinformation. Second, the migration problem includes a lot of associated issues such as ethical issues (e.g., vulnerable to exploitation by employers, low wages, work in unsafe conditions, discrimination, and marginalization), legal issues (e.g., immigration laws and policies, visa regulations and border controls, limited access to justice), social security (e.g., social protection, mental support, integration, language barriers, and cultural differences, social isolation), and the problems of reporting to the public the appropriate policies to support Ukrainian migrants in their countries of destination and to address the root causes of migration in Ukraine itself. The official and unofficial information on social media that covers all these issues are supposed to be considered in the microproject.

Therefore, the development of an actionable AI-based approach for determining information trustworthiness (i) will serve to expand understanding of the core information needs of citizens in communication with the government in the context of migration issues in the last year; and potential causes and nature of that information untrustworthiness in social media; and (ii) can support the government to develop relevant guidelines to oversee social media, and instruments to assess, analyze and monitor implementation and compliance with ELS principles in social media.

Results Summary

Using a text analytics approach such as BERTopic topic modeling, we analyzed text messages published on Telegram channels from February 2022 to September 2023, revealing 12 challenges facing Ukrainian migrants. Furthermore, our study delves into these challenges distribution across 6 major European countries with significant migrant populations, providing insights into regional differences. Additionally, temporal changes in 8 narrative themes in discussions of Ukrainian migration, extracted from official government websites, were examined. Together, this research contributes (1) to demonstrating how analytics-driven methodology can potentially be used to extract in-depth knowledge from textual data freely available on social media; and (2) to a deeper understanding of the various issues affecting the adaptation of Ukrainian migrants in European countries. The study also provides recommendations to improve programs and policies to better.  

Tangible Outcomes

1. Nina Khairova, Nina Rizun, Charalampos Alexopoulos, Magdalena Ciesielska, Arsenii Lukashevskyi, Ivan Redozub/Understanding the Ukrainian Migrants Challenges in the EU: A Topic Modeling Approach/Proceedings of the 25th Annual International Conference on Digital Government Research, 2024, 196-205 p. https://dl.acm.org/doi/abs/10.1145/3657054.3657252
2. The SOMTUME dataset contains textual information gathered from social media and news sites, comprising two segments: Trustworthiness Information Content (TIC) and Uncertain Information Content (UIC). The texts pertain to the migration of Ukrainians to the European Union from February 2022,  to August 2023. https://github.com/ninakhairova/SOMTUME
3. The results “Understanding the Ukrainian Migrants’ Challenges in the EU: A Topic Modeling Approach” of the microproject  were presented at the 25th Annual International Conference on Digital Government Research (dg.o 2024), held from June 11–14, 2024, at National Taiwan University in Taipei, Taiwan. https://dgsociety.org/dgo-2024/program/