Bot Datasets on Twitter: Analysis and Challenges

Luis Daniel Samper-Escalante,Octavio Loyola-González,Miguel Angel Medina-Pérez,Raúl Monroy

doi:10.3390/app11094105

Luis Daniel Samper-Escalante, Octavio Loyola-González + Show 2 more

Open Access

https://doi.org/10.3390/app11094105

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Abstract

The reach and influence of social networks over modern society and its functioning have created new challenges and opportunities to prevent the misuse or tampering of such powerful tools of social interaction. Twitter, a social networking service that specializes in online news and information exchange involving billions of users world-wide, has been infested by bots for several years. In this paper, we analyze both public and private databases from the literature of bot detection on Twitter. We summarize their advantages, disadvantages, and differences, recommending which is more suitable to work with depending on the necessities of the researcher. From this analysis, we present five distinct behaviors in automated accounts exhibited across all the bot datasets analyzed from these databases. We measure their level of presence in each dataset using a radar chart for visual comparison. Finally, we identify four challenges that researchers of bot detection on Twitter have to face when using these databases from the literature.

Highlights

Twitter: Analysis and Challenges.Social networks have been expanding by leaps and bounds since the last decade [1].Their reach and influence over modern society and its functioning have created opportunities for traditional and relatively new professions, as well as challenges to prevent the misuse or tampering of such powerful tools of social interaction [2].One of these new challenges has arisen in the form of a software application known as bot
We present the methodology followed and results obtained from our analysis on different labeled databases from the literature focused on bot detection
The database created by Cresci et al [34] in 2015 is the oldest of all four that we have analyzed, the inclusion of follower/following relationships gives clear advantages over the others: it allows researchers to examine the social structure of the Twitter accounts directly by implementing social network analysis (SNA) techniques or calculating graph metrics

Summary

Introduction

Twitter: Analysis and Challenges.Social networks have been expanding by leaps and bounds since the last decade [1].Their reach and influence over modern society and its functioning have created opportunities for traditional and relatively new professions, as well as challenges to prevent the misuse or tampering of such powerful tools of social interaction [2].One of these new challenges has arisen in the form of a software application known as bot. Social networks have been expanding by leaps and bounds since the last decade [1]. Their reach and influence over modern society and its functioning have created opportunities for traditional and relatively new professions, as well as challenges to prevent the misuse or tampering of such powerful tools of social interaction [2]. One of these new challenges has arisen in the form of a software application known as bot. When bots are programmed to interact with each other, they can form a botnet to carry out more complex tasks [5]

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