Skip to main content

Communication Based on Unilateral Preference on Twitter: Internet Luring in Japan

  • Conference paper
  • First Online:
Book cover Social Informatics (SocInfo 2018)

Abstract

In this paper, we focus on unilateral preference for a group of specific kind of persons as a factor of network formation. Homophily and preferential attachment explain a large part of the formation of online social networks (OSN). Unilateral preference is also assumed to have important roles in OSNs, where high searchability exists with no geographical restriction. To observe unilateral preferences in a social network, we analyzed a user network constructed through interaction between those who make Japanese tweet(s) about “runaway” and those who react to them. In this case, a large proportion of the tweets are assumed to be made by young girls and most of the latter are adult men. By observing the user network, the network is found to have unsurprisingly bipartite structure composed of a thousand former users and several thousand latter users. In spite of a few friendship links among these users, about 19% of users in the latter group take one-to-many communication with users in the former group. Therefore, communications that assumed to be based on unilateral preference exist on a considerable scale. The proportion of reply message between users that regarded to have an intention of luring is surprisingly high (61%). Furthermore, we extract the core of communication by applying k-core network analysis. As a result, the proportion of luring in the core of the network is significantly higher than outside of the k-core network.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Hampton, K.N.: Internet use and the concentration of disadvantage: glocalization and the urban underclass. Am. Behav. Sci. 53(8), 1111–1132 (2010)

    Article  Google Scholar 

  2. Kwak, H., Lee, C., Park, H., Moon, S.: What is Twitter, a social network or a news media? In: Proceedings of the 19th International Conference on World Wide Web, pp. 591–600. ACM (2010)

    Google Scholar 

  3. O’Keeffe, G.S., Clarke-Pearson, K.: The impact of social media on children, adolescents, and families. Pediatrics 127(4), 800–804 (2011)

    Article  Google Scholar 

  4. Cheng, J., Danescu-Niculescu-Mizil, C., Leskovec, J.: Antisocial behavior in online discussion communities. In: ICWSM, pp. 61–70 (2015)

    Google Scholar 

  5. Griffiths, C.K.J.: Japanese man arrested after body parts found in cooler. CNN (2017)

    Google Scholar 

  6. Albert, R., Barabási, A.L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74(1), 47 (2002)

    Article  MathSciNet  Google Scholar 

  7. Pastor-Satorras, R., Castellano, C., Van Mieghem, P., Vespignani, A.: Epidemic processes in complex networks. Rev. Mod. Phys. 87(3), 925 (2015)

    Article  MathSciNet  Google Scholar 

  8. Guille, A., Hacid, H., Favre, C., Zighed, D.A.: Information diffusion in online social networks: a survey. ACM SIGMOD Rec. 42(2), 17–28 (2013)

    Article  Google Scholar 

  9. Wang, P., Xu, B., Wu, Y., Zhou, X.: Link prediction in social networks: the state-of-the-art. Sci. China Inf. Sci. 58(1), 1–38 (2015)

    Google Scholar 

  10. Xie, J., Kelley, S., Szymanski, B.K.: Overlapping community detection in networks: the state-of-the-art and comparative study. ACM Comput. Surv. (CSUR) 45(4), 43 (2013)

    Article  Google Scholar 

  11. Kempe, D., Kleinberg, J., Tardos, É.: Maximizing the spread of influence through a social network. In: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 137–146. ACM (2003)

    Google Scholar 

  12. Liu, Y., Tang, M., Zhou, T., Do, Y.: Core-like groups result in invalidation of identifying super-spreader by k-shell decomposition. Sci. Rep. 5, 9602 (2015)

    Article  Google Scholar 

  13. Newman, M.E.: Assortative mixing in networks. Phys. Rev. Lett. 89(20), 208701 (2002)

    Article  Google Scholar 

  14. Lee, S.: Effect of online dating on assortative mating: evidence from south korea. J. Appl. Econ. 31(6), 1120–1139 (2016)

    Article  MathSciNet  Google Scholar 

  15. Myers, S.A., Sharma, A., Gupta, P., Lin, J.: Information network or social network?: the structure of the twitter follow graph. In: Proceedings of the 23rd International Conference on World Wide Web, pp. 493–498. ACM (2014)

    Google Scholar 

  16. Doughty, M., Rowland, D., Lawson, S.: Who is on your sofa?: TV audience communities and second screening social networks. In: Proceedings of the 10th European Conference on Interactive TV and Video, pp. 79–86. ACM (2012)

    Google Scholar 

  17. Beguerisse-Díaz, M., Garduno-Hernández, G., Vangelov, B., Yaliraki, S.N., Barahona, M.: Interest communities and flow roles in directed networks: the Twitter network of the UK riots. J. Royal Soc. Interface 11(101), 20140940 (2014)

    Article  Google Scholar 

  18. Hitsch, G.J., Hortaçsu, A., Ariely, D.: Matching and sorting in online dating. Am. Econ. Rev. 100(1), 130–63 (2010)

    Article  Google Scholar 

  19. Curington, C.V., Lin, K.H., Lundquist, J.H.: Positioning multiraciality in cyberspace: treatment of multiracial daters in an online dating website. Am. Sociol. Rev. 80(4), 764–788 (2015)

    Article  Google Scholar 

  20. Mascheroni, G., Ólafsson, K.: Net Children Go Mobile: Risks and Opportunities. Educatt, Milano (2014)

    Google Scholar 

  21. Livingstone, S., Haddon, L., Görzig, A., Ólafsson, K.: Risks and safety on the internet: the perspective of European children: full findings and policy implications from the EU kids online survey of 9–16 year olds and their parents in 25 countries. EU Kids Online (2011)

    Google Scholar 

  22. DeHart, D., et al.: Internet sexual solicitation of children: a proposed typology of offenders based on their chats, e-mails, and social network posts. J. Sex. Aggression 23(1), 77–89 (2017)

    Article  Google Scholar 

  23. Ortega, E.G., Baz, B.O.: Minors’ exposure to online pornography: prevalence, motivations, contents and effects. (la exposición de los menores a la pornografía en internet: prevalencia, motivaciones, contenidos y efectos). Anales de Psicología/Annals of Psychol. 29(2), 319–327 (2013)

    Google Scholar 

  24. Tener, D., Wolak, J., Finkelhor, D.: A typology of offenders who use online communications to commit sex crimes against minors. J. Aggression Maltreatment Trauma 24(3), 319–337 (2015)

    Article  Google Scholar 

  25. Babchishin, K.M., Hanson, R.K., VanZuylen, H.: Online child pornography offenders are different: a meta-analysis of the characteristics of online and offline sex offenders against children. Arch. Sex. Behav. 44(1), 45–66 (2015)

    Article  Google Scholar 

  26. Magaletta, P.R., Faust, E., Bickart, W., McLearen, A.M.: Exploring clinical and personality characteristics of adult male internet-only child pornography offenders. Int. J. Offender Therapy Comp. Criminol. 58(2), 137–153 (2014)

    Article  Google Scholar 

  27. Steel, C.M.: Web-based child pornography: the global impact of deterrence efforts and its consumption on mobile platforms. Child Abuse Negl. 44, 150–158 (2015)

    Article  Google Scholar 

  28. Seidman, S.B.: Network structure and minimum degree. Soc. Netw. 5(3), 269–287 (1983)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kimitaka Asatani .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Asatani, K., Kawahata, Y., Toriumi, F., Sakata, I. (2018). Communication Based on Unilateral Preference on Twitter: Internet Luring in Japan. In: Staab, S., Koltsova, O., Ignatov, D. (eds) Social Informatics. SocInfo 2018. Lecture Notes in Computer Science(), vol 11185. Springer, Cham. https://doi.org/10.1007/978-3-030-01129-1_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-01129-1_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01128-4

  • Online ISBN: 978-3-030-01129-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics