Narrative of governing emigration
A case study in Hong Kong
Bibliographic Data
| ID | 7843629 |
|---|---|
| Authors | Ka Wang Kelvin Lam (0000-0002-9091-5153, University of Hong Kong), Eric Fong (0000-0003-1147-0182, University of Hong Kong, corresponding author), Xinxin Wang (0000-0003-4043-1916, Yale University) |
| Year | 2025 |
| Volume | 51 |
| Issue | 18 |
| Pages | 4726-4743 |
| Publication date | 2025-11-08 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | New Community (JOURNAL) |
| Journal identifiers | ISSN: 0047-9586 • E-ISSN: 1469-9451 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/1369183x.2025.2544087 |
| OpenAlex | W4414004601 |
| Language | EN |
| Citations received | 3 |
| References cited | 28 |
Understanding media narratives helps us better understand how diverse actors in society attempt to shape public opinion. The reports of government officials’ announcements and discussions, as well as articles published by political figures and opinion influencers in major newspapers, provide an important complement to policy narratives about an event. Our study examines the media narrative surrounding the recent emigration wave in Hong Kong following the large-scale social unrest in 2019. We utilised the Latent Dirichlet Allocation (LDA), a generative statistical model, which provides an efficient and effective method for the analysis of large-scale textual data. Analysing reports and articles from five major Chinese newspapers in Hong Kong, published between January 2020 and December 2022, we identified five major themes. These themes shed light on the strategies used to interpret the emigration phenomenon
Demographic economics · Economic geography · Economics · Emigration · Genealogy · Geography · Linguistics · Narrative · Political science · Sociology · Diaspora, migration, transnational identity · Gender Studies · History · Law · Migration and Labor Dynamics · Migration, Refugees, and Integration · Philosophy
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| Unique citing works | 3 |
|---|---|
| Citations per year | 3 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |