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Attitudes Towards Migration in a COVID-19 Context: Testing a Behavioral Immune System Hypothesis with Twitter Data

Yerka Freire-Vidal, Gabriela Fajardo, Carlos Rodríguez-Sickert, Eduardo Graells-Garrido, José Antonio Muñoz-Reyes, Oriana Figueroa

Abstract

The COVID-19 outbreak implied many changes in the daily life of most of the world's population for a long time, prompting severe restrictions on sociality. The Behavioral Immune System (BIS) suggests that when facing pathogens, a psychological mechanism would be activated that, among other things, would generate an increase in prejudice and discrimination towards marginalized groups, including immigrants. This study aimed to test if people tend to enhance their rejection of minorities and foreign groups under the threat of contagious diseases, using the users' attitudes towards migrants in Twitter data from Chile, for pre-pandemic and pandemic contexts. Our results only partially support the BIS hypothesis, since threatened users increased their tweet production in the pandemic period, compared to empathetic users, but the latter grew in number and also increased the reach of their tweets between the two periods. We also found differences in the use of language between these types of users. Alternative explanations for these results may be context-dependent.

Attitudes Towards Migration in a COVID-19 Context: Testing a Behavioral Immune System Hypothesis with Twitter Data

Abstract

The COVID-19 outbreak implied many changes in the daily life of most of the world's population for a long time, prompting severe restrictions on sociality. The Behavioral Immune System (BIS) suggests that when facing pathogens, a psychological mechanism would be activated that, among other things, would generate an increase in prejudice and discrimination towards marginalized groups, including immigrants. This study aimed to test if people tend to enhance their rejection of minorities and foreign groups under the threat of contagious diseases, using the users' attitudes towards migrants in Twitter data from Chile, for pre-pandemic and pandemic contexts. Our results only partially support the BIS hypothesis, since threatened users increased their tweet production in the pandemic period, compared to empathetic users, but the latter grew in number and also increased the reach of their tweets between the two periods. We also found differences in the use of language between these types of users. Alternative explanations for these results may be context-dependent.
Paper Structure (13 sections, 2 equations, 6 figures, 3 tables)

This paper contains 13 sections, 2 equations, 6 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Methodology
  3. Dataset Description
  4. Classifier of Attitudes
  5. Results
  6. General Description of Attitudes
  7. Reach and Influence of Empathetic and Threatened Users
  8. Vocabulary Analysis
  9. Discussion
  10. Conclusions
  11. Appendix
  12. Keywords used for filtering
  13. Methodological details of XGBoost

Figures (6)

  • Figure 3: Daily volume of tweets in the data set (on the left is the pre-pandemic period, and on the right is the post-pandemic period).
  • Figure 4: Percentage distribution of users, classified by attitude for each period of analysis. Left: users present in both periods ($n =$ 21.469). Right: users with more than 14 tweets in total, considering both period ($n =$ 5,312)
  • Figure 5: Number of users classified in each attitude, for the pre- and post-pandemic period, and their attitude changes.
  • Figure 6: Daily distribution of average attitude scores (empathy and threat), for both periods. Top: pre-pandemic period. Bottom: post-pandemic period.
  • Figure 7: Top-50 words with relative frequency per attitude, pre- and post-pandemic (left and right, respectively).
  • ...and 1 more figures