7,045 research outputs found
Automatic Detection of Online Jihadist Hate Speech
We have developed a system that automatically detects online jihadist hate
speech with over 80% accuracy, by using techniques from Natural Language
Processing and Machine Learning. The system is trained on a corpus of 45,000
subversive Twitter messages collected from October 2014 to December 2016. We
present a qualitative and quantitative analysis of the jihadist rhetoric in the
corpus, examine the network of Twitter users, outline the technical procedure
used to train the system, and discuss examples of use.Comment: 31 page
Hate is not Binary: Studying Abusive Behavior of #GamerGate on Twitter
Over the past few years, online bullying and aggression have become
increasingly prominent, and manifested in many different forms on social media.
However, there is little work analyzing the characteristics of abusive users
and what distinguishes them from typical social media users. In this paper, we
start addressing this gap by analyzing tweets containing a great large amount
of abusiveness. We focus on a Twitter dataset revolving around the Gamergate
controversy, which led to many incidents of cyberbullying and cyberaggression
on various gaming and social media platforms. We study the properties of the
users tweeting about Gamergate, the content they post, and the differences in
their behavior compared to typical Twitter users.
We find that while their tweets are often seemingly about aggressive and
hateful subjects, "Gamergaters" do not exhibit common expressions of online
anger, and in fact primarily differ from typical users in that their tweets are
less joyful. They are also more engaged than typical Twitter users, which is an
indication as to how and why this controversy is still ongoing. Surprisingly,
we find that Gamergaters are less likely to be suspended by Twitter, thus we
analyze their properties to identify differences from typical users and what
may have led to their suspension. We perform an unsupervised machine learning
analysis to detect clusters of users who, though currently active, could be
considered for suspension since they exhibit similar behaviors with suspended
users. Finally, we confirm the usefulness of our analyzed features by emulating
the Twitter suspension mechanism with a supervised learning method, achieving
very good precision and recall.Comment: In 28th ACM Conference on Hypertext and Social Media (ACM HyperText
2017
The Alt-Right and Global Information Warfare
The Alt-Right is a neo-fascist white supremacist movement that is involved in
violent extremism and shows signs of engagement in extensive disinformation
campaigns. Using social media data mining, this study develops a deeper
understanding of such targeted disinformation campaigns and the ways they
spread. It also adds to the available literature on the endogenous and
exogenous influences within the US far right, as well as motivating factors
that drive disinformation campaigns, such as geopolitical strategy. This study
is to be taken as a preliminary analysis to indicate future methods and
follow-on research that will help develop an integrated approach to
understanding the strategies and associations of the modern fascist movement.Comment: Presented and published through IEEE 2019 Big Data Conferenc
Hate Speech on Social Media Networks: Towards a Regulatory Framework?
Social networks serve as effective platforms in which users’ ideas can be spread in an easy and efficient manner. However, those ideas can be hateful and harmful, some of which may even amount to hate speech. YouTube, Facebook and Twitter have internal regulatory policies in relation to hate speech and have signed a Code of Conduct on the regulation of illegal hate speech with the European Commission. This paper looks at the issue of tackling hate speech on social networks and argues that, notwithstanding the weaknesses of internal policies and their implementation, their existence, as facilitated by the Code of Conduct, serves as a light at the end of the Internet hate tunnel where issues of multiple jurisdictions as well as technological realities, such as mirror sites and more, have resulted in the task of online regulation being more than a daunting one
- …