Mapping Insights from News Articles to Tackle Low Birth Rate and Parenthood in Finland
Wang, Xiaowen; Oussalah, Mourad; Niemela, Mika; Ristikari, Tiina (2024-01-09)
Wang, Xiaowen
Oussalah, Mourad
Niemela, Mika
Ristikari, Tiina
Springer
09.01.2024
Wang, X., Oussalah, M., Niemela, M. et al. Mapping Insights from News Articles to Tackle Low Birth Rate and Parenthood in Finland. SN COMPUT. SCI. 5, 172 (2024). https://doi.org/10.1007/s42979-023-02492-8
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© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
https://creativecommons.org/licenses/by/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202402231964
https://urn.fi/URN:NBN:fi:oulu-202402231964
Tiivistelmä
Abstract
The aim of this study is to explore how parenthood and birth rate is manifested in Finnish society and citizens as revealed by automated mining of news articles from Finland News API. Several levels of analysis were conducted using natural language processing and text mining techniques to unfold relevant insights from the collected News API. This includes surface-level analysis, word frequency-based analysis, topic-based analysis, and health ontology mapping. In total, 1621 news articles were selected and analyzed from the collected dataset. The surface-level analysis revealed the capacity of imminent health researchers to gain public audience and interest. Content-based analysis revealed the importance of family, employment, and health issues. Topical analysis stressed on the dominance of family issues during corona time, followed by public services and employment issues. Finally, the health ontology mapping revealed the quasi dominance of mental health and development disorders concerns. The research work provides a general framework for analyzing unstructured text to extract useful insights that can help policymakers to positively impact the existing policy in health and social policy development.
The aim of this study is to explore how parenthood and birth rate is manifested in Finnish society and citizens as revealed by automated mining of news articles from Finland News API. Several levels of analysis were conducted using natural language processing and text mining techniques to unfold relevant insights from the collected News API. This includes surface-level analysis, word frequency-based analysis, topic-based analysis, and health ontology mapping. In total, 1621 news articles were selected and analyzed from the collected dataset. The surface-level analysis revealed the capacity of imminent health researchers to gain public audience and interest. Content-based analysis revealed the importance of family, employment, and health issues. Topical analysis stressed on the dominance of family issues during corona time, followed by public services and employment issues. Finally, the health ontology mapping revealed the quasi dominance of mental health and development disorders concerns. The research work provides a general framework for analyzing unstructured text to extract useful insights that can help policymakers to positively impact the existing policy in health and social policy development.
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