A visual recommendation system for co-authorship social networks (ChinaVis 2018)

Yan, Kai; Cui, Wei

doi:10.1007/s12650-018-0528-9

Cited by 2 publications

(1 citation statement)

References 28 publications

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“…This section expands on the analysis of author co-citations, which entail incidents where two works simultaneously appear in other literature, reflecting a co-citation relationship. This analysis established the connections among authors by identifying authors who are co-cited by a set of publications [78]- [80]. The co-citation network for this bibliometric analysis is shown in Figure 4, where it consists of the top three clusters among 1095 nodes and 250 links.…”

Section: E Number Of Author's Co-citationmentioning

confidence: 99%

Social Media Recommender Systems (SMRS): A Bibliometric Analysis Study 2000–2021

et al. 2022

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The increasing popularity of social media resources such as blogs, bookmarks, chatrooms, forums and video portals in recent years has attracted diverse users. Following the rise of the Internet, online content has become overloaded, prompting the introduction of recommender systems on social media. As a result, research on the dynamic growth of recommender systems in social media has gained significant traction since the year 2000. Social media recommender systems (SMRS) utilize multiple recommendation fields such as item, user, location, tag, event, tour and game in searching for preferred recommended information. Thus, young research fellows, academic scholars and practitioners must understand the need for SMRS to be complemented with recommendation fields. This requirement underlines the significance of a bibliometric analysis that focuses on social media based on existing publications. Hence, using the Web of Science (WoS) database, this study aimed to gather statistical information on SMRS to help researchers acquire an extensive understanding of such systems. The analysis was conducted by identifying SMRS-related publications and scientometric indicators to assess the growth rate, including the relative growth rate (RGR), doubling time (DT) and the field-normalized citation score (NCSf)-for citation analysis. Overall, this bibliometric study provides relevant measures for comparing and improving the citation rate of publications for new researchers.

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Section: E Number Of Author's Co-citationmentioning

confidence: 99%