Search (3 results, page 1 of 1)

  • × author_ss:"Cho, H."
  • × year_i:[2020 TO 2030}
  1. Moulaison-Sandy, H.; Adkins, D.; Bossaller, J.; Cho, H.: ¬An automated approach to describing fiction : a methodology to use book reviews to identify affect (2021) 0.00
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    Abstract
    Subject headings and genre terms are notoriously difficult to apply, yet are important for fiction. The current project functions as a proof of concept, using a text-mining methodology to identify affective information (emotion and tone) about fiction titles from professional book reviews as a potential first step in automating the subject analysis process. Findings are presented and discussed, comparing results to the range of aboutness and isness information in library cataloging records. The methodology is likewise presented, and how future work might expand on the current project to enhance catalog records through text-mining is explored.
    Type
    a
  2. Cho, H.; Disher, T.; Lee, W.-C.; Keating, S.A.; Lee, J.H.: Facet analysis of anime genres : the challenges of defining genre information for popular cultural objects (2020) 0.00
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    Abstract
    Anime, as a growing form of multimedia, needs a better and more thorough organization for its myriad unique terminologies. Existing studies show patrons' desire to search and get recommendations for anime. However, due to inadequate indexing and often confusing or inaccurate usage of terms, searching and acquiring recommendations remain challenging. Our research seeks to close the gap and make discovery and recommendations more viable. In this study, we conducted a facet analysis of anime genre terms that are currently used in thirty-six anime-related English-language databases and websites. Using a card sorting method with an inductive approach to the 1,597 terms collected, we identified and defined nine facets and 153 foci terms that describe different genres of anime. Identified terms can be implemented within different organizational systems including library catalogs, recommendation systems, and online databases to improve genre definitions and search experiences.
    Type
    a
  3. Cho, H.; Pham, M.T.N.; Leonard, K.N.; Urban, A.C.: ¬A systematic literature review on image information needs and behaviors (2022) 0.00
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    Abstract
    Purpose With ready access to search engines and social media platforms, the way people find image information has evolved and diversified in the past two decades. The purpose of this paper is to provide an overview of the literature on image information needs and behaviors. Design/methodology/approach Following an eight-step procedure for conducting systematic literature reviews, the paper presents an analysis of peer-reviewed work on image information needs and behaviors, with publications ranging from the years 1997 to 2019. Findings Application of the inclusion criteria led to 69 peer-reviewed works. These works were synthesized according to the following categories: research methods, users targeted, image types, identified needs, search behaviors and search obstacles. The reviewed studies show that people seek and use images for multiple reasons, including entertainment, illustration, aesthetic appreciation, knowledge construction, engagement, inspiration and social interactions. The reviewed studies also report that common strategies for image searches include keyword searches with short queries, browsing, specialization and reformulation. Observed trends suggest common deployment of query analysis, survey questionnaires and undergraduate participant pools to research image information needs and behavior. Originality/value At this point, after more than two decades of image information needs research, a holistic systematic review of the literature was long overdue. The way users find image information has evolved and diversified due to technological developments in image retrieval. By synthesizing this burgeoning field into specific foci, this systematic literature review provides a foundation for future empirical investigation. With this foundation set, the paper then pinpoints key research gaps to investigate, particularly the influence of user expertise, a need for more diverse population samples, a dearth of qualitative data, new search features and information and visual literacies instruction.
    Type
    a