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Complex Network Analysis in Python by Dmitry Zinoviev

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Understand Similarity

Similarity-based networks emerge from the similarity of one or more attributes of objects represented by the network nodes. The type of objects and the number of attributes are limited only by the creativity of the network researchers. (This is not to say that your limitless imagination, rather than your experience, should guide your research.) The nodes may represent people (age, gender, language, skin color), products (price, color, shape, material), companies (industry, size, country, the form of ownership), and so on. It is your job to choose the “right” definition of similarity that at least does not contradict common sense.

Any quantitative measure of similarity has two aspects: what to measure and how to measure. ...

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