Published In
2019 Portland International Conference on Management of Engineering and Technology (PICMET)
Document Type
Article
Publication Date
2019
Subjects
System analysis, Online social networks -- Effect of size on, Social networks -- Analysis, Twitter (Firm)
Abstract
A study of the online social networks of six Twitter conversations about six YouTube product categories reveals that directionality and network size affect the structure of online social networks. Our results indicate that large networks tend to be non-random, regardless of whether they are directional or not, suggesting that structural attributes of the online networks under study are a true reflection of network's features. Smaller non-directional networks also tend to be non-random, whereas smaller directional networks tend to be random in nature. However, very small networks tend to be random in nature, whether they are directional or not. Our results suggest that larger online networks undergo different generation mechanisms than smaller real-world networks, especially if these networks are directional. Extant theory, which is almost exclusively derived from observation of real-world networks, may thus not adequately describe the behavior of online networks. We propose research to remedy this deficiency at the end of this paper.
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DOI
10.23919/PICMET.2019.8893732
Persistent Identifier
https://archives.pdx.edu/ds/psu/32735
Citation Details
N. Mayande and C. Weber, "Do Directionality and Network Size Affect Network Structure in Online Social Networks?," 2019 Portland International Conference on Management of Engineering and Technology (PICMET), Portland, OR, USA, 2019, pp. 1-18.
Description
This is the publisher's final PDF. Copyright 2019 by PICMET. Paper delivered at the 2019 Proceedings of PICMET '19: Technology Management in the World of Intelligent Systems