Centrality: Data Set vs Network
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2 سال پیش
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This video shows the differences,
This video shows the differences, but also similarities, between the central tendency of a data set and the centrality of a network and includes an exercise to refresh your knowledge of central tendency measurements.
DATA SET
Usually, data sets are large and difficult to understand. Fortunately, there are central tendency measures such as mode, median and mean that can help us. These descriptive statistics give us easy-to-understand information about the data set and show the big picture. We explain these statistics in the video.
NETWORK
In a network we not only have data points, so-called nodes, but also links between them. Usually, these networks are large and hard to fathom.
Fortunately, there are also measures of centrality for a network that can help us understand this network and show the bigger picture.
CENTRALIZATION VS CENTRALITY
The centrality in a network can be measured at different levels: network, group, node and link. The idea of network centrality is to measure the overall centralization of a network and refers to properties of the network structure as a whole. So, centralization does not refer to the relative importance of nodes, but to the overall coherence of a network. Therefore, to avoid confusion, we talk in this video about network centralization and group, node or link centrality.
DESCRIPTIVE STATISTICS
Central tendency of a set of data points and network centralization are both descriptive statistics. These statistics summarize and organize characteristics of a data set and a network, respectively. Both reflect the centre of the data distribution and are general statistics that summarize the data set.
DATA SET CENTRAL TENDENCY
Well known central tendency of a set with data points are mode, median and mean. Let's refresh these concepts in the video.
NETWORK CENTRALIZATION
We can not only measure the central tendency of a data set, but also the overall centralization of a network. Some resemble the central tendency of a data set, while others are more complicated to calculate. Some examples: central node, centre, network core, closeness centralization or average node centrality.
NODE CENTRALITY
Most common centrality measurements are node centralities, these come in many flavours. Although these are NO descriptive statistics, there are analogies to be drawn with central tendency measurements of a data set. We explain this in the video.
📽️ What is Network Centrality? What is Network Centrality?
SENSITIVITY
The mean is more sensitive to outliers than the mode or median. Centrality measurements of networks can also be sensitive. When we add or remove links, the node centrality may change. Centralities based on the shortest path are usually more sensitive than local measurements such as degree centrality.
CONCLUSION
In this video we saw that the central tendency of a data set and network centralization are both descriptive statistics. Both summarize the set by reflecting the centre.
Although centralities are not descriptive statistics, there analogies to be drawn with central tendency. Like mode, mode and mean, different centralization and centrality measurements have also different properties and applications.
TIMESTAMPS
00:00 Introduction
00:16 Data set
00:45 Network
01:14 Centralization vs centrality
01:42 Descriptive statistics
02:11 Exercise: refresh mode, median and mean
04:11 Network: centralization
04:34 Node centrality
05:30 Sensitivity
05:59 Conclusion
VIDEOS IN THIS SERIES 🎞️
📽️ Why Network Analysis 🤔🧐: Why Network Analysis?
📽️ How Symbio6 Improves Your Business 🤝📈🤩: How Symbio6 Improves Your Business 🤝📈🤩
Get started with network analysis today! It has never been so easy to improve your business, we are 😀 to help you. https://symbio6.nl/en/
ABOUT US
Symbio6 gets the best out of relational data to help organizations perform even better. We do this by helping to discover, collect, store, analyse and visualize relational data and convert this into concrete actions to 📈 your business. https://symbio6.nl/en/about-us
#nodecentrality #startnetworkanalysistoday #symbio6
CONTRIBUTIONS
DATA SET
Usually, data sets are large and difficult to understand. Fortunately, there are central tendency measures such as mode, median and mean that can help us. These descriptive statistics give us easy-to-understand information about the data set and show the big picture. We explain these statistics in the video.
NETWORK
In a network we not only have data points, so-called nodes, but also links between them. Usually, these networks are large and hard to fathom.
Fortunately, there are also measures of centrality for a network that can help us understand this network and show the bigger picture.
CENTRALIZATION VS CENTRALITY
The centrality in a network can be measured at different levels: network, group, node and link. The idea of network centrality is to measure the overall centralization of a network and refers to properties of the network structure as a whole. So, centralization does not refer to the relative importance of nodes, but to the overall coherence of a network. Therefore, to avoid confusion, we talk in this video about network centralization and group, node or link centrality.
DESCRIPTIVE STATISTICS
Central tendency of a set of data points and network centralization are both descriptive statistics. These statistics summarize and organize characteristics of a data set and a network, respectively. Both reflect the centre of the data distribution and are general statistics that summarize the data set.
DATA SET CENTRAL TENDENCY
Well known central tendency of a set with data points are mode, median and mean. Let's refresh these concepts in the video.
NETWORK CENTRALIZATION
We can not only measure the central tendency of a data set, but also the overall centralization of a network. Some resemble the central tendency of a data set, while others are more complicated to calculate. Some examples: central node, centre, network core, closeness centralization or average node centrality.
NODE CENTRALITY
Most common centrality measurements are node centralities, these come in many flavours. Although these are NO descriptive statistics, there are analogies to be drawn with central tendency measurements of a data set. We explain this in the video.
📽️ What is Network Centrality? What is Network Centrality?
SENSITIVITY
The mean is more sensitive to outliers than the mode or median. Centrality measurements of networks can also be sensitive. When we add or remove links, the node centrality may change. Centralities based on the shortest path are usually more sensitive than local measurements such as degree centrality.
CONCLUSION
In this video we saw that the central tendency of a data set and network centralization are both descriptive statistics. Both summarize the set by reflecting the centre.
Although centralities are not descriptive statistics, there analogies to be drawn with central tendency. Like mode, mode and mean, different centralization and centrality measurements have also different properties and applications.
TIMESTAMPS
00:00 Introduction
00:16 Data set
00:45 Network
01:14 Centralization vs centrality
01:42 Descriptive statistics
02:11 Exercise: refresh mode, median and mean
04:11 Network: centralization
04:34 Node centrality
05:30 Sensitivity
05:59 Conclusion
VIDEOS IN THIS SERIES 🎞️
📽️ Why Network Analysis 🤔🧐: Why Network Analysis?
📽️ How Symbio6 Improves Your Business 🤝📈🤩: How Symbio6 Improves Your Business 🤝📈🤩
Get started with network analysis today! It has never been so easy to improve your business, we are 😀 to help you. https://symbio6.nl/en/
ABOUT US
Symbio6 gets the best out of relational data to help organizations perform even better. We do this by helping to discover, collect, store, analyse and visualize relational data and convert this into concrete actions to 📈 your business. https://symbio6.nl/en/about-us
#nodecentrality #startnetworkanalysistoday #symbio6
CONTRIBUTIONS
2 سال پیش
در تاریخ 1400/11/10 منتشر شده
است.
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