The Re-mediation of Legacy and New Media on Twitter : A Six-Language Comparison of the European Social Media Discourse on Migration
Farjam, Mike LU and Dutceac Segesten, Anamaria LU
(2024)
In Social Science Computer Review
- Abstract
Scholarly literature has demonstrated that hybridity transforms both legacy and new media, but that this change is not even. We treat social media platforms as arenas of remediation, where users share and add their own context to information produced by both media subtypes and compare social media conversations about migration in six European languages that include links to either traditional or new media during 2015–2019. We use a mix of computational and statistical methods to analyze 3.5 million (re)tweets and 500,000 links shared within them. We identify the main differences in agenda setting power, function, and tone present within tweets that include links to legacy or new media. Our results show that discourses are similar across... (More)
Scholarly literature has demonstrated that hybridity transforms both legacy and new media, but that this change is not even. We treat social media platforms as arenas of remediation, where users share and add their own context to information produced by both media subtypes and compare social media conversations about migration in six European languages that include links to either traditional or new media during 2015–2019. We use a mix of computational and statistical methods to analyze 3.5 million (re)tweets and 500,000 links shared within them. We identify the main differences in agenda setting power, function, and tone present within tweets that include links to legacy or new media. Our results show that discourses are similar across languages but clearly different when remediating legacy and new media. Trust in legacy media is correlated with higher proportion of shared links from legacy media and reversely related to the proportion of shared links from new media sources. Considering the volume and timing of the remediated content, we conclude that legacy media retains its agenda setting power. New media linked content tends to cover migration in association to subjects such as Islam or terrorism and to express strong critical opinions against migrants/refugees. The language used is more toxic than in legacy media linked content. The tweets remediating legacy media articles covered topics like domestic or European politics, causes of refugee arrivals and procedures to give them protection. Thus, legacy and new media remediated content differs in both tone and function: toxicity is low and factuality high for content linking to legacy media, with the reverse being true for new media remediations.
(Less)
- author
- Farjam, Mike
LU
and Dutceac Segesten, Anamaria
LU
- organization
- publishing date
- 2024
- type
- Contribution to journal
- publication status
- epub
- subject
- keywords
- Bayesian network, comparative research, computational analysis, European politics, migration, multilingual analysis, social media
- in
- Social Science Computer Review
- pages
- 24 pages
- publisher
- SAGE Publications
- external identifiers
-
- scopus:85190894107
- ISSN
- 0894-4393
- DOI
- 10.1177/08944393241246101
- project
- The Right to International Protection: A Pendulum Between Globalization and Nativization?
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © The Author(s) 2024.
- id
- 02773e9f-8a7c-4bb0-80a8-96a5a85a83eb
- date added to LUP
- 2024-06-04 18:20:35
- date last changed
- 2024-06-18 11:21:57
@article{02773e9f-8a7c-4bb0-80a8-96a5a85a83eb,
abstract = {{<p>Scholarly literature has demonstrated that hybridity transforms both legacy and new media, but that this change is not even. We treat social media platforms as arenas of remediation, where users share and add their own context to information produced by both media subtypes and compare social media conversations about migration in six European languages that include links to either traditional or new media during 2015–2019. We use a mix of computational and statistical methods to analyze 3.5 million (re)tweets and 500,000 links shared within them. We identify the main differences in agenda setting power, function, and tone present within tweets that include links to legacy or new media. Our results show that discourses are similar across languages but clearly different when remediating legacy and new media. Trust in legacy media is correlated with higher proportion of shared links from legacy media and reversely related to the proportion of shared links from new media sources. Considering the volume and timing of the remediated content, we conclude that legacy media retains its agenda setting power. New media linked content tends to cover migration in association to subjects such as Islam or terrorism and to express strong critical opinions against migrants/refugees. The language used is more toxic than in legacy media linked content. The tweets remediating legacy media articles covered topics like domestic or European politics, causes of refugee arrivals and procedures to give them protection. Thus, legacy and new media remediated content differs in both tone and function: toxicity is low and factuality high for content linking to legacy media, with the reverse being true for new media remediations.</p>}},
author = {{Farjam, Mike and Dutceac Segesten, Anamaria}},
issn = {{0894-4393}},
keywords = {{Bayesian network; comparative research; computational analysis; European politics; migration; multilingual analysis; social media}},
language = {{eng}},
publisher = {{SAGE Publications}},
series = {{Social Science Computer Review}},
title = {{The Re-mediation of Legacy and New Media on Twitter : A Six-Language Comparison of the European Social Media Discourse on Migration}},
url = {{http://dx.doi.org/10.1177/08944393241246101}},
doi = {{10.1177/08944393241246101}},
year = {{2024}},
}