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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/8677
Title: Your Tribe Decides Your Vibe: Analyzing Local Popularity in the US Patent Citation Network
Authors: Narang, Nishit
Keywords: Computer Science
Social and Information Networks
Neural networks
Issue Date: Jun-2021
Publisher: ARXIV
Abstract: In many networks, the indegree of a vertex is a measure of its popularity. Past research has studied indegree distributions treating the network as a whole. In the US Patent citation network (USPCN), patents are classified into categories and subcategories. A natural question arises: How do patents gather their popularity from various (sub)categories? We analyse local indegree distributions to answer this question. The citation (indegree) of a patent within the same category indicates its internal popularity, while a cross-category citation indicates its external popularity. We analyze the internal and external indegree distributions at each level of USPCN hierarchy to learn how the internal and external popularity of patents varies across (sub)categories. We find that all (sub)categories have local preferences that decide internal and external patents' popularities. Different patents are popular in different groups: Groups C1, C2 and C3 may not agree on popular patents in C1. In general, patent popularity appears to be a highly local phenomenon with subcategories (not even categories) deciding their own popular patents independent of the other (sub)categories
URI: https://arxiv.org/abs/2106.01148
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/8677
Appears in Collections:Department of Computer Science and Information Systems

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