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Abstract

Twitter has emerged as a popular source of sharing and delivering news information. In tweet messages, URLs to web resources and hashtags are often included. This study investigates the potential of the hyperlinks and hashtags as topical clues and indicators to tweet messages. For this study, we crawled and analyzed about 1.5 million tweets for a 3-month period covering any topic or subject. The findings of this study revealed a power law relationship for the ranking and frequency of (a) the host names of URLs, and (b) a pair of hashtags and URLs that appeared in the tweet messages. This study also discovered that the most popular URLs used in tweets come from news and media websites, and a majority of the hyperlinked resources are news web pages. One implication of this study is that Twitter users are becoming more active in sharing already published information than producing new information. Finally, our investigation on hashtags for web resource indexing reveals that hashtags have the potential to be used as indexing terms for co-occurring URLs in the same tweet. We also discuss the implications of this study for web resource recommendation.

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Abstract

Based on text mining, this study explored topics in the research domain of knowledge organization. A text corpus consisting of titles and abstracts was generated from 282 articles of the Knowledge Organization journal for the recent ten years from 2006 to 2015. Term frequency analysis and Latent Dirichlet allocation topic modeling were employed to analyze the collected corpus. Topic modeling uncovered twenty research topics prevailing in the knowledge organization field, including theories and epistemology, classification scheme, domain analysis and ontology, digital archiving, document indexing and retrieval, taxonomy and thesaurus system, metadata and controlled vocabulary, ethical issues, and others. In addition, topic trends over the tenyears were examined to identify topics that attracted more discussion in the journal. The top two topics that received increased attention recently were "ethical issues in knowledge organization" and "domain analysis and ontologies." This study yields insight into a better understanding of the research domain of knowledge organization. Moreover, text mining approaches introduced in this study have methodological implications for domain analysis in knowledge organization.