During the COVID‐19 pandemic of 2020–2021, public library leaders across the United States were forced to make decisions quickly that affected the services and resources they were able to provide. However, the health information they had to make decisions on was imperfect and constantly changing. Interviews with 23 public library managers and directors revealed that more authoritative local data was needed for decision‐making and to share with their service populations. Overwhelmed public health system and/or suspicious or skeptical political environments hindered access to locally‐specific health information. Several respondents were uncomfortable creating information or making decisions without the guidance of health officials. Additionally, the library managers and directors described working as crisis managers, making decisions that impacted the health of their staff and their communities. In capturing and analyzing these “pandemic decision‐making stories,” this research informs future library information responses to community needs during times of crisis.
PurposeReaders articulate mood in deeply subjective ways, yet the underlying structure of users' understanding of the media they consume has important implications for retrieval and access. User articulations might at first seem too idiosyncratic, but organizing them meaningfully has considerable potential to provide a better searching experience for all involved. The current study develops mood categories inductively for fiction organization and retrieval in information systems.Design/methodology/approachThe authors developed and distributed an open-ended survey to 76 fiction readers to understand their preferences with regard to the affective elements in fiction. From the fiction reader responses, the research team identified 161 mood terms and used them for further categorization.FindingsThe inductive approach resulted in 30 categories, including angry, cozy, dark and nostalgic. Results include three overlapping mood families: Emotion, Tone/Narrative, and Atmosphere/Setting, which in turn relate to structures that connect reader-generated data with conceptual frameworks in previous studies.Originality/valueThe inherent complexity of “mood” should not dissuade researchers from carefully investigating users' preferences in this regard. Adding to the existing efforts of classifying moods conducted by experts, the current study presents mood terms provided by actual end-users when describing different moods in fiction. This study offers a useful roadmap for creating taxonomies for retrieval and description, as well as structures derived from user-provided terms that ultimately have the potential to improve user experience.
Video games reflect the current culture and society. Games stand as points of transmission that reflect cultural trends and social norms, although not comprehensively. While it seems that more games have tried to be inclusive of diverse gender and sexual identities recently, there is still a lack of studies that discuss how real video game players see LGBTQ+ inclusive games. To understand the game players’ perceptions in this regard, this study qualitatively analyzes online video game review postings from Steam, focusing on user reviews of gender and sexuality inclusive games. Based on four gender and sexuality inclusive video games selected, we collected 400 user-generated video game reviews as our dataset. Our findings identified 22 primary themes, including Mood/Emotions, Social/Cultural Importance and Representation. This paper further discusses some of the critical topics discovered, such as identity, conflicts in game communities and representation.
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