Nothing Special   »   [go: up one dir, main page]

Skip to main content

Advertisement

Log in

Diffusion of pro- and anti-false information tweets: the Black Panther movie case

  • SBP-BRiMS 2018
  • Published:
Computational and Mathematical Organization Theory Aims and scope Submit manuscript

Abstract

Much has been made of the importance of the speed at which disinformation diffuses through online social media and this speed is an important aspect to consider when designing interventions. An additional complexity is that there can be different types of false information that travel from and through different communities who respond in various ways within the same social media conversation. Here we present a case study/example analysis exploring the speed and reach of three different types of false stories found in the Black Panther movie Twitter conversation and comparing the diffusion of these stories with the community responses to them. We find that the negative reaction to fake stories of racially-motivated violence whether in the form of debunking quotes or satirical posts can spread at speeds that are magnitudes higher than the original fake stories. Satire posts, while less viral than debunking quotes, appear to have longer lifetimes in the conversation. We also found that the majority of mixed community members who originally spread fake stories switched to attacking them. Our work serves as an example of the importance of analyzing the diffusion of both different types of disinformation and the different responses to it within the same overall conversation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Arif A, Robinson JJ, Stanek SA, Fichet ES, Townsend P, Worku Z, Starbird K (2017) A closer look at the self-correcting crowd: examining corrections in online rumors. In: Proceedings of the 2017 ACM conference on computer supported cooperative work and social computing. ACM, p 155–168

  • Babcock M, Beskow DM, Carley KM (2018) Beaten up on Twitter? Exploring fake news and satirical responses during the Black Panther movie event. In: International conference on social computing, behavioral–cultural modeling and prediction and behavior representation in modeling and simulation. Springer, p 97–103

  • Beskow D, Carley K Bot-hunter a tiered approach to detecting and characterizing automated activity on Twitter. http://sbp-brims.org/2018/proceedings/papers/latebreaking_papers/LB_5.pdf

  • Castillo C, Mendoza M, Poblete B (2011) Information credibility on Twitter. In: Proceedings of the 20th international conference on world wide web. ACM, p 675–684

  • Del Vicario M, Quattrociocchi W, Scala A, Zollo F (2018) Polarization and fake news: early warning of potential misinformation targets. arXiv preprint arXiv:1802.01400

  • Hoang TBN, Mothe J (2017) Predicting information diffusion on Twitter–analysis of predictive features. J Comput Sci 28:257–264

    Article  Google Scholar 

  • Karsai M, Kivelá M, Pan RK, Kaski K, Kertész J, Barabási AL, Saramáki J (2011) Small but slow world: how network topology and burstiness slow down spreading. Phys Rev E 83(2):025102

    Article  Google Scholar 

  • Kitsak M, Gallos LK, Havlin S, Liljeros F, Muchnik L, Stanley HE, Makse HA (2010) Identification of influential spreaders in complex networks. Nat Phys 6(11):888

    Article  Google Scholar 

  • Lazer DM, Baum MA, Benkler Y, Berinsky AJ, Greenhill KM, Menczer F, Metzger MJ, Nyhan B, Pennycook G, Rothschild D (2018) The science of fake news. Science 359(6380):1094–1096

    Article  Google Scholar 

  • Ribeiro MH, Calais PH, Almeida VA, Meira Jr W (2017) “everything i disagree with is# fakenews”: correlating political polarization and spread of misinformation. arXiv preprint arXiv:1706.05924

  • Tandoc EC Jr, Lim ZW, Ling R (2018) Defining fake news a typology of scholarly definitions. Digit Journal 6(2):137–153

    Article  Google Scholar 

  • Twitter (2018) ‘black panther’ is most tweeted about movie ever. https://wtop.com/social-media/2018/03/twitter-black-panther-is-most-tweeted-about-movie-ever/

  • Vosoughi S, Roy D, Aral S (2018) The spread of true and false news online. Science 359(6380):1146–1151

    Article  Google Scholar 

  • Xiong F, Liu Y, Zhang Z, Zhu J, Zhang Y (2012) An information diffusion model based on retweeting mechanism for online social media. Phys Lett A 376(30–31):2103–2108

    Article  Google Scholar 

  • Yang J, Counts S (2010) Predicting the speed, scale, and range of information diffusion in Twitter. In: ICWSM 2010, vol 10, p 355–358

  • Yang J, Leskovec J (2010) Modeling information diffusion in implicit networks. In: 2010 IEEE 10th international conference on data mining (ICDM). IEEE, p 599–608

  • Zhao Q, Erdogdu MA, He HY, Rajaraman A, Leskovec J (2015) Seismic: a self-exciting point process model for predicting tweet popularity. In: Proceedings of the 21st ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 1513–1522

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Matthew Babcock.

Appendix

Appendix

See Table 3.

Table 3 Half and full-life (99% ) of top false stories and responses

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Babcock, M., Cox, R.A.V. & Kumar, S. Diffusion of pro- and anti-false information tweets: the Black Panther movie case. Comput Math Organ Theory 25, 72–84 (2019). https://doi.org/10.1007/s10588-018-09286-x

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10588-018-09286-x

Keywords

Navigation