Reference

@inproceedings{Freitas2015@asonam,

author = {Freitas, Carlos and Benevenuto, Fabricio and Ghosh, Saptarshi and Veloso, Adriano},

title = {Reverse Engineering Socialbot Infiltration Strategies in Twitter},

booktitle = {Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining},

series = {ASONAM '15},

year = {2015}

}

Database Files

Profiles: CSV file containing the bot profiles during the experiment period.

● bot_id: Id of the bot

● followers_count: Number of followers of the bot at the crawled time.

● friends_count: Number of friends of the bot at the crawled time.

● klout: Klout score of the bot at the crawled time.

● crawled_timestamp: Timestamp for the crawl.

Interactions: CSV file containing the bots interactions during the experiment period.

● bot_id: Id of the bot.

● interaction_with: If the interaction occurred with a target user, a regular user or another bot.

● interaction_type: Type of the interaction (e.g., follow, retweet, etc).

● date: Date of the interaction.

BotHelper Class:

We provided a python class that returns the bot properties given a bot_id. Example of use:

>>> from bot_helper import *

>>> bh = BotHelper()

>>> bh.Gender(1)

'm'

>>> bh.Group(49)

1

>>> bh.Activity(49)

'h'