On Twitter Bots Behaving Badly:

A Manual and Automated Analysis of Python Code Patterns on GitHub

Keywords: Bots, Harm, Abuse, Code patterns, Pattern recognition, GitHub, Twitter, Python

Abstract

Bots, i.e., algorithmically driven entities that behave like humans in on-line communications, are increasingly infiltrating social conversations on the Web. If not properly prevented, this presence of bots may cause harm to the humans they interact with. This article aims to understand which types of abuse may lead to harm and whether these can be considered intentional or not. We manually review a dataset of 60 Twitter bot code repositories on GitHub, derive a set of potentially abusive actions, characterize them using a taxonomy of abstract code patterns, and assess the potential abusiveness of the patterns. The article then describes the design and implementation of a code pattern recognizer and uses the pattern recognizer to automatically analyze a dataset of 786 Python bot code repositories. The study does not only reveal the existence of 28 communication-specific code patterns - which could be used to assess the harmfulness of bot code - but also their consistent presence throughout all studied repositories.

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Author Biographies

Florian Daniel, Politecnico di Milano, Via Ponzio 34/5, 20133 Milan, Italy

Florian Daniel is an associate professor at the Dipartimento di Elettronica, Informazione e Bioingegneria of Politecnico di Milano since January 2016, where he currently teaches the foundations of programming to Management Engineering students. He is expected to obtain his tenure as associate professor in January 2019. Before, he held post-doc/research fellow positions in Politecnico di Milano (2007-2008) and University of Trento (2008-2005). He worked as visiting researcher in HP Labs, Palo Alto, California (2006), and the University of New South Wales, Sydney, Australia (2013, 2015, 2017), and as visiting professor in the Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS), Porto Alegre, Brazil (2015).

Andrea Millimaggi, Politecnico di Milano, Via Ponzio 34/5, 20133 Milan, Italy

Florian Daniel is an Associate Professor with Politecnico di Milano, Italy. His research interests include bots/chatbots, social data analysis and knowledge extraction, service-oriented computing, business process management, and blockchain. He received the Ph.D. degree in information technology from Politecnico di Milano.

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Published
2020-01-23
Section
ICWE2019