| Autor: |
Ruiz Segarra, Ana, Suárez, Juan-Luis |
| Zdroj: |
Social Network Analysis & Mining; 11/12/2021, Vol. 12 Issue 1, p1-14, 14p |
| Abstrakt: |
This article proposes to detect topic-based communities by analyzing the language that YouTube creators use to tag their channels. We downloaded a set of tags of YouTube video game-related channels using the most popular video game titles of 2016 as queries. We compare the tags of the channels to create a network of channel tags' similarity. The resulting network helped us to discover topic-based communities of popular video game channels in YouTube in 2016. Then, we analyzed the connections of the network to understand how channels grouped around popular and complex topics such as 'let play,' a video format popular in the platform in 2016. Our discoveries add knowledge on how individual tagging practices help in the formation of communities around topics in YouTube. We argue that through the analysis of channels' tags, we will get a better understanding of how gaming channels in YouTube helped in the creation of topic-based communities at a large scale through the individual use of tags. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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