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  • × author_ss:"Zhang, M."
  1. Wang, X.; Zhang, M.; Fan, W.; Zhao, K.: Understanding the spread of COVID-19 misinformation on social media : the effects of topics and a political leader's nudge (2022) 0.05
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    Abstract
    The spread of misinformation on social media has become a major societal issue during recent years. In this work, we used the ongoing COVID-19 pandemic as a case study to systematically investigate factors associated with the spread of multi-topic misinformation related to one event on social media based on the heuristic-systematic model. Among factors related to systematic processing of information, we discovered that the topics of a misinformation story matter, with conspiracy theories being the most likely to be retweeted. As for factors related to heuristic processing of information, such as when citizens look up to their leaders during such a crisis, our results demonstrated that behaviors of a political leader, former US President Donald J. Trump, may have nudged people's sharing of COVID-19 misinformation. Outcomes of this study help social media platform and users better understand and prevent the spread of misinformation on social media.
  2. Zhang, M.; Zhang, Y.: Professional organizations in Twittersphere : an empirical study of U.S. library and information science professional organizations-related Tweets (2020) 0.04
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    Abstract
    Twitter is utilized by many, including professional businesses and organizations; however, there are very few studies on how other entities interact with these organizations in the Twittersphere. This article presents a study that investigates tweets related to 5 major library and information science (LIS) professional organizations in the United States. This study applies a systematic tweets analysis framework, including descriptive analytics, network analytics, and co-word analysis of hashtags. The findings shed light on user engagement with LIS professional organizations and the trending discussion topics on Twitter, which is valuable for enabling more successful social media use and greater influence.
  3. Ahn, J.-w.; Soergel, D.; Lin, X.; Zhang, M.: Mapping between ARTstor terms and the Getty Art and Architecture Thesaurus (2014) 0.03
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    Abstract
    To make better use of knowledge organization systems (KOS) for query expansion, we have developed a pattern-based technique for composition ontology mapping in a specific domain. The technique was tested in a two-step mapping. The user's free-text queries were first mapped to Getty's Art & Architecture Thesaurus (AAT) terms. The AAT-based queries were then mapped to a search engine's indexing vocabulary (ARTstor terms). The result indicated that our technique has improved the mapping success rate from 40% to 70%. We discuss also how the technique may be applied to other KOS mapping and how it may be implemented in practical systems.
    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik