Introduction Social media has created opportunities for children to gather social support online (Blackwell et al., 2016; Gonzales, 2017; Jackson, Bailey, & Foucault Welles, 2018; Khasawneh, Rogers, Bertrand, Madathil, & Gramopadhye, 2019; Ponathil, Agnisarman, Khasawneh, Narasimha, & Madathil, 2017). However, social media also has the potential to expose children and adolescents to undesirable behaviors. Research showed that social media can be used to harass, discriminate (Fritz & Gonzales, 2018), dox (Wood, Rose, & Thompson, 2018), and socially disenfranchise children (Page, Wisniewski, Knijnenburg, & Namara, 2018). Other research proposes that social media use might be correlated to the significant increase in suicide rates and depressive symptoms among children and adolescents in the past ten years (Mitchell, Wells, Priebe, & Ybarra, 2014). Evidence based research suggests that suicidal and unwanted behaviors can be promulgated through social contagion effects, which model, normalize, and reinforce self-harming behavior (Hilton, 2017). These harmful behaviors and social contagion effects may occur more frequently through repetitive exposure and modelling via social media, especially when such content goes “viral” (Hilton, 2017). One example of viral self-harming behavior that has generated significant media attention is the Blue Whale Challenge (BWC). The hearsay about this challenge is that individuals at allmore »
Raiders of the lost kek: 3.5 years of augmented 4chan posts from the politically incorrect board
This paper presents a dataset with over 3.3M threads and
134.5M posts from the Politically Incorrect board (/pol/) of
the imageboard forum 4chan, posted over a period of almost
3.5 years (June 2016–November 2019). To the best of our
knowledge, this represents the largest publicly available 4chan
dataset, providing the community with an archive of posts that
have been permanently deleted from 4chan and are otherwise
inaccessible. We augment the data with a set of additional
labels, including toxicity scores and the named entities mentioned in each post. We also present a statistical analysis of the
dataset, providing an overview of what researchers interested
in using it can expect, as well as a simple content analysis,
shedding light on the most prominent discussion topics, the
most popular entities mentioned, and the toxicity level of each
post. Overall, we are confident that our work will motivate
and assist researchers in studying and understanding 4chan, as
well as its role on the greater Web. For instance, we hope this
dataset may be used for cross-platform studies of social media,
as well as being useful for other types of research like natural
language processing. Finally, our dataset can assist qualitative
work focusing on in-depth case studies of specific narratives,
events, or social theories.
- Award ID(s):
- 1942610
- Publication Date:
- NSF-PAR ID:
- 10212018
- Journal Name:
- Proceedings of the International AAAI Conference on Weblogs and Social Media
- ISSN:
- 2334-0770
- Sponsoring Org:
- National Science Foundation
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