2:00pm - 2:15pmID: 155
/ PS-23: 1
Short Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/Topics: Data Science; Analytics; and VisualizationKeywords: Future work sentences; Construction of task systems; Content analysis
Using Future Work Sentences to Explore Research Trends of Different Tasks in a Special Domain
Yuchen Qian, Zhicheng Li, Wenke Hao, Yuzhuo Wang, Chengzhi Zhang
Nanjing University of Science and Technology, People's Republic of China
Research trend detection is an important topic for scientific researchers. Future work sentences (FWS) , as direct descriptions of future research, aren’t fully utilized in research trend detection. Therefore, this article uses FWS to investigate research trends of different tasks in a particular domain. Taking the conference papers in the natural language processing (NLP) field as our research objects, we obtain the FWS in each paper to build the corpus and classified them into 6 main types. After that, the task of each paper is annotated, and a task system with 29 categories is constructed to compare the FWS in different tasks. The results show that the proportion of method mentioned in FWS is the highest, and different tasks focus on different FWS types: emerging tasks need more resources, while mature tasks prefer method and application. This study provides researchers a reference to understand the research trend of specific tasks and is helpful to compare different tasks.
2:15pm - 2:30pmID: 162
/ PS-23: 2
Short Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/Topics: Information TheoryKeywords: Bibliographic Entities; BIBFRAME; Linked Data; Data Mining; Fp-growth
Publisher References in Bibliographic Entity Descriptions
Jim Hahn
University of Pennsylvania, USA
This paper describes a method for improved access to publisher references in linked data RDF editors using data mining techniques and a large corpus of library metadata encoded in the MARC21 standard. The corpus is comprised of clustered sets of publishers and publisher locations from the library MARC21 records found in the Platform for Open Data (POD). POD is a data aggregation project involving member institutions of the IvyPlus Library Confederation and contains seventy million MARC21 records, forty million of which are unique. The discovery of publisher entity sets described forms the basis for the streamlined description of BIBFRAME Instance entities. The result of this work includes a database of association rules and RDF editor improvements. The association rules are the basis of a prototype autosuggestion feature of BIBFRAME Instance entity description properties designed specifically to support the auto-population of publisher entities in linked data RDF editors.
2:30pm - 2:45pmID: 124
/ PS-23: 3
Short Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/Topics: Library and Information ScienceKeywords: Archival item-level metadata, named entity disambiguation, Wikidata, linked data, entity management
Named Entity Disambiguation for Archival Collections: Metadata, Wikidata, and Linked Data
Katherine Polley, Vivian Tompkins, Brendan Honick, Jian Qin
Syracuse University, USA
Representing archival metadata as linked data can increase the findability and usability of items, and linked data sources such as Wikidata can be used to further enrich existing collection metadata. However, a central challenge to this process is the named entity disambiguation or entity linking that is required to ensure that the named entities in a collection are being properly matched to Wikidata entities so that any additional metadata is applied correctly. This paper details our experimentation with one entity linking system called OpenTapioca, which was chosen for its use of Wikidata and its accessibility to librarians and archivists with minimal technical intervention. We discuss the results of using OpenTapioca for named entity disambiguation on the Belfer Cylinders Collection from the Special Collections Research Center at Syracuse University, highlighting the successes and limitations of the system and of using Wikidata as a knowledge base.
2:45pm - 3:00pmID: 170
/ PS-23: 4
Short Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/Topics: Library and Information ScienceKeywords: Subject representation, Metadata evaluation, Metadata change, Bibliographic metadata
Patterns of Subject Metadata Change in MARC 21 Bibliographic Records for Video Recordings
Vyacheslav Zavalin1, Oksana Zavalina2, Rachel Safa1
1Texas Woman's University, USA; 2University of North Texas, USA
Study reported in this paper analyzed over 20 thousand of machine-readable library metadata records in MARC 21 bibliographic format that are based on Resource Description and Access (RDA) standard. The focus of this analysis is on change in subject metadata – data elements designed for representing the aboutness of information objects – over a 6-year period between 2014 and 2020. The analyzed dataset is the entire population of the records representing English-language video recordings in DVD format in WorldCat database as of one year after official transition to RDA data content standard in library metadata creation. Analysis of metadata representing audiovisual materials is needed as audiovisual metadata practices tend to differ from those for other materials due to high occurrence of unique resources. The study includes quantitative and qualitative analyses into the change in the application of data elements (fields and subfields) over time and categorizes the observed change.
3:00pm - 3:30pmID: 231
/ PS-23: 5
Long Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/Topics: Social Media and Social ComputingKeywords: Social media, misinformation, digital forensics, image compression, memes
Forensic Analysis of Memetic Image Propagation: Introducing the SMOC BRISQUEt Method
James Hodges1, Mitch Chaiet2, Praful Gupta1
1The University of Texas at Austin, USA; 2Harvard Kennedy School Shorenstein Center, USA
This paper introduces a mixed-methods approach for forensically reconstructing the propagation of visual media via networked digital devices. The authors present case studies drawn from political misinformation around the January 6, 2021 riots at the U.S. Capitol. Using interpretive analysis, the authors identify traces of user interfaces that remain in images being shared about the riots. Using computational analysis, the authors evaluate compression levels in digital photographs of the events in question, thus identifying which instances of the image are closer to the source (as well as which images appear to be identical). By combining these two approaches, the authors argue that SMOC BRISQUEt refines our understanding of misinformation’s memetic spread.
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