Social network datasets and citation network datasets
- Citation Author(s):
-
Chen Xiaocong
- Submitted by:
- CHEN Xiaocong
- Last updated:
- DOI:
- 10.21227/ratd-a340
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Abstract
Social Network Datasets (SNDs) are structured data collected from social media platforms, online communities, or communication networks for the study of user behavior, information dissemination, community discovery, and so on. This kind of data usually contains nodes (users/entities) and edges (relationships/interactions), and is widely used in the fields of social network analysis (SNA), recommender systems, and public opinion monitoring.
Citation network datasets are network data constructed through citation relationships between academic papers, patents, or other documents, and are used to study knowledge dissemination, academic influence, disciplinary evolution, etc.
Instructions:
Social network datasets typically contain the following types:
1.Nodes data (Nodes): entities such as users, pages, groups, etc., with attached attributes (e.g., age, gender, interests).
2.Edges: relationships between users (e.g., friends, followers, interactions).
3.Content: User-generated text, images, videos, etc.
4.Temporal data (Temporal): timestamps of interactions or relationship establishment.
Citation Network Datasets's Data types and structure
(1) Basic data
Literature metadata: title, author, year of publication, journal/conference name.
Citation relationship: directed edge (A→B means A cites B).
(2) Extended attributes
Text content: abstract, keywords, full text (provided in some datasets).
Author/institution information: Construct the author cooperation network (Co-authorship Network).
(3) Network Types
Static network: citation relationship within a fixed time frame.
Dynamic Network: contains timestamps, citation evolution can be analyzed (e.g. DBLP-Citation-network)
