Social media use and anti-immigrant attitudes: evidence from a survey and automated linguistic analysis of Facebook posts

ABSTRACT

Social media has a role to play in shaping the dynamic relations between immigrants and citizens. This study examines the effects of threat perceptions, consumptive and expressive use of social media, and political trust on attitudes against immigrants in Singapore. Study 1, based on a survey analysis (N = 310), suggests that symbolic but not realistic threat perception, is positively associated with anti-immigrant attitudes. The consumptive use of social media and political trust is negatively related to anti-immigrant attitudes. Moderation analyses suggest that consumptive social media use has negative consequences for individuals with increased symbolic threat perception and high political trust. But is there a correspondence between consumptive and expressive use of social media in terms of predicting prejudicial attitudes? Study 2 benchmarks the survey findings against participants’ opinion expression via Facebook posts (N = 146,332) discussing immigrants. Automated linguistic analyses reveal that self-reported survey measures correlate with the expressive use of social media for discussing immigrants. Higher anti-immigrant attitudes are associated with higher negative sentiment, anger, and swear words in discussing immigrants. The findings highlight the need to pay attention to the combined influence of social media use and individual political beliefs when analyzing intergroup relations.

KEYWORDS:

• Social media
• political trust
• threat perceptions
• prejudice
• anti-immigrant

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 We also examined the two-way interactions between political trust and threat perceptions in predicting anti-immigrant attitudes. The results were statistically not significant.

2 LIWC’s emotion lexica calculate the proportion of positive and negative sentiment for each piece of text. We also calculated the average proportion of anger, swear words, and religiosity by applying the appropriate lexica from LIWC 2015. In this manner, four measures of sentiment and religiosity were obtained as percentage proportions, where a higher score indicates that a greater proportion of each message comprises of positive, negative, anger, or swear words. In this manner, we obtained an average score of positive sentiment, negative sentiment, anger, swearing, and religiosity towards foreigners for each user. A Singlish sentiment lexicon does exist (Ho, Hamzah, Poria, & Cambria, 2018); however, it focuses solely on Singaporean slang words and provides no measurements for anger and religiosity. Therefore, it was not suitable to measure the facets of emotion that were critical to building a theoretical understanding of prejudice.

Additional information

Funding

This work was supported by MINISTRY OF EDUCATION SINGAPORE [grant number MOE2017-T2-2-145].

Notes on contributors

Saifuddin Ahmed

Saifuddin Ahmed is an assistant professor at Wee Kim Wee School of Communication and Information, Nanyang Technological University. Dr. Ahmed’s research interests lie in new and emerging media, political communication, election studies, comparative studies, and public opinion.

Vivian Hsueh Hua Chen

Vivian Hsueh Hua Chen is an associate professor at Wee Kim Wee School of Communication and Information, Nanyang Technological University. Dr. Chen’s research areas include social interaction in virtual communities, impacts of communication technology, intercultural communication, intergroup relations, technology affordance, and gamification for social wellbeing.

Kokil Jaidka

Kokil Jaidka is an assistant professor at the Department of Communications and New Media, National University of Singapore. Her research interests lie in examining the role of social media platforms in enabling self-presentation and social behavior and in developing computational models of language for the measurement and understanding of computer-mediated communication.

Rosalie Hooi

Rosalie Hooi is currently an independent researcher. When she worked on the current project, she was a postdoctoral researcher at Wee Kim Wee School of Communication and Information, Nanyang Technological University.

Arul Chib

Arul Chib is an associate professor at Wee Kim Wee School of Communication and Information at Nanyang Technological University in Singapore. Dr. Chib investigates the impact of mobile phones in healthcare (mHealth) and transnational migration issues and is particularly interested in issues of gender.