An Evaluation of 2023 Australia’s New Immigration Policy for New Zealand Citizens Based on Online Public Opinion
- DOI
- 10.2991/978-94-6463-542-3_41How to use a DOI?
- Keywords
- Australia Immigration policy; online public opinion; sentiment analysis; LDA analysis
- Abstract
Public opinion is always an important effect that influences the direction of countries’ immigration policy while the evaluation of immigration policy based on online public opinion has a significant theoretical and practical means. This project adopts a sentiment analysis and LDA analysis to evaluate the attitude of online public opinion toward Australia’s 2023 new immigration policy for New Zealand citizens and identify the main public concerns about this policy. For the new policy in 2023, harvest public opinion information, maintain the natural language processing technology to analyze internet public opinion. Research on public attitudes and attention about the new policy from sentiment score and Latent Dirichlet Allocation analysis. Based on the results of that two-analysis method, this project then raises related suggestions for Australia policymakers in their future immigration policy-making.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Fangxuan Wang AU - Yimou Han PY - 2024 DA - 2024/10/15 TI - An Evaluation of 2023 Australia’s New Immigration Policy for New Zealand Citizens Based on Online Public Opinion BT - Proceedings of the 2024 2nd International Conference on Management Innovation and Economy Development (MIED 2024) PB - Atlantis Press SP - 334 EP - 348 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-542-3_41 DO - 10.2991/978-94-6463-542-3_41 ID - Wang2024 ER -