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Session Overview
Session
Paper Session 23: Data and Representation
Time:
Tuesday, 02/Nov/2021:
2:00pm - 3:30pm

Session Chair: Jian Qin, Syracuse University, USA
Location: Salon J, Lobby Level, Marriott


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Presentations
2:00pm - 2:15pm
ID: 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 Visualization
Keywords: 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 - 2:30pm
ID: 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 Theory
Keywords: 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 - 2:45pm
ID: 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 Science
Keywords: 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 - 3:00pm
ID: 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 Science
Keywords: 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 - 3:30pm
ID: 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 Computing
Keywords: 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.