Towards efficient and reliable utilization of automated data collection: Media scrapers applied to news on climate change
Year: 2024
Type: article
Abstract: : Automated data collection provides tempting opportunities for social sciences and humanities studies. Abundant data accumulating in various digital archives allows more comprehensive, timely and cost-efficient ways of harvesting and processing information. While easing or even removing some of the key problems, such as laborious and time-consuming data collection and potential errors and biases related to subjective coding of materials and distortions caused by focus on small samples, automated methods also bring in new risks such as poor understanding of contexts of the data or non-recognition of underlying systematic errors or missing information. Results from testing different methods to collect data describing newspaper coverage of climate change in Finland emphasize that fully relying on automatable tools such as media scrapers has its limitations and can provide comprehensive but incomplete document acquisition for research. Many of these limitations can, however, be addressed and not all of them rely on manual control.
DOI: 10.46298/jdmdh.13123
Authors: Erkki Mervaala, Jari Lyytimäki
Institution: Finnish Environment Institute
Language: English
Subfield: General Social Sciences
Field: Social Sciences
Domain: Social Sciences
SDG: Climate action
Open Access status: diamond
OpenAlex ID: W4396534802