watch-complexity - npm Package Compare versions

Comparing version 0.0.1 to 0.1.0

index.js

 'use strict';
 
-// Requirements
-const influence_typology = require('./algorithms/influence/influence');
-
-
 // Modules to export
 module.exports = {
   influence: {
-    typology: influence_typology
+    typology: require('./algorithms/influence/typology/main')
+  },
+  network:{
+    similarity: require('./algorithms/network/similarity/main')
   }
 };

libs/helpers.js

@@ -31,2 +31,5 @@ 'use strict';
 
+// Sum values for reduce array
+const sum = (x, y) => x + y;
+
 module.exports = {
@@ -36,3 +39,4 @@ euclidean_distance,
   extremes_values,
-  memory_usage
+  memory_usage,
+  sum
 };

package.json

 {
   "name": "watch-complexity",
-  "version": "0.0.1",
+  "version": "0.1.0",
   "description": "Artificial Intelligence from experimental research on computational social science.",
@@ -12,3 +12,11 @@ "license": "MIT",
     "social science",
-    "socialscience"
+    "socialscience",
+    "communication science",
+    "machine learning",
+    "ML",
+    "data science",
+    "datascience",
+    "humanities",
+    "research",
+    "computational social science"
   ],
@@ -32,3 +40,3 @@ "author": "davidemiceli",
   ],
-  "homepage": "https://github.com/davidemiceli/watch-complexity#readme",
+  "homepage": "https://davidemiceli.github.io/watch-complexity",
   "directories": {
@@ -35,0 +43,0 @@ "algorithms": "algorithms",

README.md

 # Watch Complexity
 Artificial Intelligence from experimental research on computational social science.
 
-## Ranked influence typology
+## Description
+WatchComplexity is a Machine Learning framework to understand and analyze complex networks and more in general complex data. It is a collection of _**clustering techniques**_ inspired by social science and communication theories.
 
-### Description
-Detect the type of influence that each node holds within a network.
+## Documentation
 
-The algorithm detect not only the influence played by every node inside a network, but also how it contributes to the overall network (for example the word-of-mouth, content creation, and diffusion of information).
+All useful informations can be found in the wiki documentation:
+- [**Introduction**](https://github.com/davidemiceli/watch-complexity/wiki)
+- [**Installation**](https://github.com/davidemiceli/watch-complexity/wiki/Installation)
+- [**Algorithms**](https://github.com/davidemiceli/watch-complexity/wiki/algorithms)
+- [**Testing**](https://github.com/davidemiceli/watch-complexity/wiki/testing)
 
-Given a large dataset of connections as input, it provides a ranking of all nodes by influence score, reporting their typology of influence. Every node plays a certain role in the network and affects the other nodes in its own different way.
+## Algorithms
+The tool provides the following algorithms.
 
-### Getting started
-#### Install
+- [**Ranked influence typology**](https://github.com/davidemiceli/watch-complexity/wiki/Ranked-influence-typology)  <br>*Detect the type of influence that each node holds within a network.*
+- [**Network Similarity**](https://github.com/davidemiceli/watch-complexity/wiki/Network-similarity)<br>*Measures the similarity between different networks.*
+
+## Getting started
+### Install
 ```shell
 npm install watch-complexity
 ```
-#### How to use it
+### How to use it
 ```javascript
 const watchcomplexity = require('watch-complexity');
 ```
-
-### Algorithms
-Below the list of all algorithms that can be used, with usage details.
-
-#### Ranked influence typology
-
+Example of use:
 ```javascript
-watchcomplexity.influence.typology(edges=Array[Object])
-```
-
-Field	| Type | Required	| Description
---- | --- | --- | ---
-edges	| [object] | yes | An array of all the connections between nodes.
-edges > from | string	| yes	| The node's name or id where the edge start: the source node of the link.
-edges > to | string	| yes	| The node's name or id where the edge end: the target node of the link.
-edges > weight | number	| yes	| The weight of the connection: how strong is the bond among the linked nodes.
-
-Example
-```javascript
 // The list of edges
@@ -50,3 +41,3 @@ const edges = [
 ```
-That will return:
+That will return as result:
 ```javascript
@@ -101,1 +92,7 @@ {
 ```
+
+# Motivation
+Our main goal is to do experimental research with practical applications.
+
+# License
+WatchComplexity is available under the [MIT license](https://opensource.org/licenses/MIT).

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70238

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Number of package files

21

increased by40%

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3586

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97

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