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To better meet people's information needs under the public health crisis, this study explored the information needs and seeking behavior of college students in the context of the COVID-19 pandemic.

This research utilized a survey and the convenience snowball sampling method. A sample of 400 college students was obtained.

The results revealed that college students have paid great attention to COVID-19-related information. They sought the information mainly for personal protection, obtaining the latest information and seeking information for family and friends. Their COVID-19-related information needs were diverse; at different stages, the concerns were different. Social media and mass media were both found to be the most useful tools for seeking COVID-19 information. Too much repetitive information, unclear authoritative and reliable informational sources, and difficulties in judging the authenticity of the information were the most common obstacles for them in information seeking. Nevertheless, the majority of the students agreed that they were very satisfied and somewhat satisfied with the current information services. This did not affect the students' understanding of the importance of health services provided by libraries.

Insights into the people's information needs and information-seeking behavior of this study could help the information providers to offer appropriate information in better ways to improve the public's virus protection capabilities and maintain the stability of social order.

This study aims to explore the implementation of artificial intelligence (AI) in archival practice by presenting the thoughts and opinions of working archival practitioners. It contributes to the extant literature with a fresh perspective, expanding the discussion on AI adoption by investigating how it influences the perceptions of digital archival expertise.

In this study a two-phase data collection consisting of four online focus groups was held to gather the opinions of international archives and digital preservation professionals (n = 16), that participated on a volunteer basis. The qualitative analysis of the transcripts was performed using template analysis, a style of thematic analysis.

Four main themes were identified: fitting AI into day to day practice; the responsible use of (AI) technology; managing expectations (about AI adoption) and bias associated with the use of AI. The analysis suggests that AI adoption combined with hindsight about digitisation as a disruptive technology might provide archival practitioners with a framework for re-defining, advocating and outlining digital archival expertise.

The volunteer basis of this study meant that the sample was not representative or generalisable.

Although the results of this research are not generalisable, they shed light on the challenges prospected by the implementation of AI in the archives and for the digital curation professionals dealing with this change. The evolution of the characterisation of digital archival expertise is a topic reserved for future research.