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Analyzing profile on Twitter for detect behavior of spamming bot

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spottingbot

Analyzing profile on Twitter for detect behavior of a spamming bot

spottingbot is an experimental and open-source project that needs you to evolve, do not hesitate to contribute on our GitHub repository by opening a pull request or to contact us at valentin@appcivico.com. A documentation about how the current indexes are calculated is also available here

You can also join us on our Telegram group for freely talk about suggestions, improvement or simply ask us anything

Usage

spottingbot can be used both as a command-line interface application (cli) or as an independent module

Command-line interface

Installation

npm install

Settings file

Create a .twitter.json file that contains:

{
  "consumer_key": "Your application consumer key",
  "consumer_secret": "Your application consumer secret",
  "access_token_key": "Your application access token key, only for user authentication",
  "access_token_secret": "Your application access token secret, only for user authentication"
}

Both User and App-only authentication are supported, for App-only, the Bearer token will be automatically requested

Start

npm start username

or

source/cli.js username

username have to be replaced by the profile to analyze

Install bin locally on your system

npm link sudo might be necessary

Then

spottingbot username

Module

Call

const spottingbot = require('spottingbot');

spottingbot(username, twitter_config, index);

username is a string that contains the screen name of the Twitter profile to analyze.

twitter_config is an object that contains Twitter credentials, both User and App-only authentication are supported, for App-only, the Bearer token will be automatically requested, the twitter_config object should be like:

{
  consumer_key: "Your application consumer key",
  consumer_secret: "Your application consumer secret",
  access_token_key: "Your application access token key", // Only for User authentication
  access_token_secret: "Your application access token secret" // Only for User authentication
}

index is used for disabling some index, it is an object that looks like

{
  user: true,
  friend: true,
  temporal: true,
  network: true
}

By default, and if omitted, everything is true.

To disabling only one index, this is not necessary to put everything in the object, {friend: false}, is correct.

Return value

spottingbot handle both callback style and node promise style

Callback
spottingbot(username, twitter_config, index, function(error, result) {
  if (error) {
    // Handle error
    return;
  }
  // Do something with result
})
Promise
spottingbot(username, twitter_config, index)
  .then(result => {
    // Do something with result
  })
  .catch(error => {
    // Handle error
  })
Value

The return value is an object that contains

{
  metadata: {
    count: 1 // Always 1 for now
  },
  profiles: [
     {
       username: 'screen_name',
       url: 'https://twitter.com/screen_name',
       avatar: 'image link',
       language_dependent: {
         sentiment: {
           value: 0.65
         }
       },
       language_independent: {
         friend: 0.19,
         temporal: 0.37,
         network: 0.95,
         user: 0
       },
       bot_probability: {
         all: 0.37
       },
       user_profile_language: 'en',
     }
  ]
}

spottingbot is a project inspired by Botometer, an OSoMe project.

This project is part of the PegaBot initiative.

PegaBot is a project of the Institute of Technology and Society of Rio de Janeiro (ITS Rio), Instituto Equidade & Tecnologia and AppCívico.

spottingbot is an experimental and open-source project that needs you to evolve, do not hesitate to contribute on our GitHub repository by opening a pull request or to contact us at valentin@appcivico.com. A documentation about how the current indexes are calculated is also available here

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