Network Basics: Points, Lines, and Positions
Abstract
This chapter presents an introduction to the basic concepts central to social network analysis. Written for those with little experience in the approach, the chapter aims to provide the necessary tools to dig deeper into exploring social networks via the subsequent chapters in this volume. It begins by introducing the building blocks of networks—nodes and edges—and their characteristics. Next, it outlines several of the major dimensions of network analysis, including the implications of boundary specification and levels of analysis. It also briefly introduces statistical approaches to networks and network data collection. The chapter concludes with a discussion of ethical issues that arise when collecting and analyzing social network data.
Integrity signals
Registry
Cites
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The general procedure was to build a graph for every time-dependent sample and use interaction (structural data sets) or semantic networks (content-considering data sets).
“Based on these two types of data sets, the general procedure was to build a graph for every time-dependent sample as social networks are dynamic networks [142] and use interaction (structural data sets) or semantic networks (content-considering data sets)”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [142]
These metrics differ by data type, granularity, and approach (connectionist vs. positional).
“These metrics differ by data type, granularity, and approach (connectionist vs. positional) [142].”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [142]
Social networks are dynamic networks.
“as social networks are dynamic networks [142]”
From A systematic review of echo chamber research: comparative analysis of conceptualizations, operationalizations, and varying outcomes (2025) · cites this paper as [142]
Cited by
Sorted by citations
Hartmann, D., Wang, S. M., Pohlmann, L., & Berendt, B. (2025) · Journal of Computational Social Science · doi:10.1007/s42001-025-00381-z · Cited by 59 · see citing works
- Authors
- Light, R., & Moody, J.
- Affiliations
- University of Oregon (US)
- Duke University (US)
- Venue
- The Oxford Handbook of Social Networks
- Publisher
- Oxford University Press
- Published
- 2020-12-15
- Pages
- 15-33
- OpenAlex
- W3117177440
- Cited by
- 10
- References
- 0
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 2 · 2022: 1
- Type
- reference entry
- Language
- en
- Open access
- closed
- Topics
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Social Sciences › Sociology and Political Science › Social Capital and Networks
- Social Sciences › Sociology and Political Science › Social Power and Status Dynamics
- Keywords
- social network analysis, network nodes, network edge, levels of analysis, network statistics, network data collection, research ethics, network position
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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