Skip to main content

Instant Messaging for Detecting Dynamic Ego-Centered Communities

  • Reference work entry
  • First Online:
  • 26 Accesses

Synonyms

Community evolution; Dynamic community detection; Temporal analysis; Temporal networks

Glossary

Dynamic Community:

a community that changes over time

Ego-Centered Community:

a community based on a targeted node called ego

Instant Messaging Networks:

a social network communication built based on the content of instant messaging

Instant Messaging:

an online chat that offers real-time text transmission over the Internet

Spatiotemporal Network:

a social network that is built based on individuals, their interaction, and their location over the time

Definition

The development of online social media has created many opportunities to communicate, access, and share information from anywhere and at anytime. The kind of application such as Viber, WhatsApp, Imo, Line, as well as Facebookaffords plenty of possibilities for getting in touch with friends, colleagues, and relatives at every moment with real-time messages, photos, videos, etc. Data collected from those applications integrate...

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   2,500.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   549.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

References

  • Bródka P, Saganowski S, Kazienko P (2013) Ged: the method for group evolution discovery in social networks. Soc Netw Anal Min 3(1):1–14

    Article  MATH  Google Scholar 

  • Cazabet R, Amblard F (2014) Dynamic community detection. In: Encyclopedia of social network analysis and mining. Springer, New York, pp 404–414

    Google Scholar 

  • Chakrabarti D, Kumar R, Tomkins A (2006) Evolutionary clustering. In: Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 554–560

    Google Scholar 

  • Chan SY, Hui P, Xu K (2009) Community detection of time-varying mobile social networks. In: Complex sciences. Springer, Berlin, Heidelberg, pp 1154–1159

    Google Scholar 

  • Chen J, Za ıane O, Goebel R (2009) Local community identification in social networks. In: International conference on advances in social network analysis and mining, 2009. ASONAM’09. IEEE, pp 237–242

    Google Scholar 

  • Clauset A (2005) Finding local community structure in networks. Phys Rev E 72(2):026,132

    Article  Google Scholar 

  • Eagle N, Pentland AS, Lazer D (2009) Inferring friendship network structure by using mobile phone data. Proc Natl Acad Sci 106(36):15,274–15,278

    Article  Google Scholar 

  • Ermentrout B (1998) Neural networks as spatio-temporal pattern-forming systems. Rep Prog Phys 61(4):353

    Article  Google Scholar 

  • Gao H, Tang J, Liu H (2012) Mobile location prediction in spatio-temporal context. In: Nokia mobile data challenge workshop 41:44

    Google Scholar 

  • Greene D, Doyle D, Cunningham P (2010) Tracking the evolution of communities in dynamic social networks. In: 2010 international conference on advances in social networks analysis and mining (ASONAM). IEEE, pp 176–183

    Chapter  Google Scholar 

  • Hopcroft J, Khan O, Kulis B, Selman B (2004) Tracking evolving communities in large linked networks. Proc Natl Acad Sci 101(suppl 1):5249–5253

    Article  Google Scholar 

  • Lancichinetti A, Fortunato S, Kert´esz J (2009) Detecting the overlapping and hierarchical community structure in complex networks. New J Phys 11(3):033,015

    Article  Google Scholar 

  • Li J, Huang L, Bai T, Wang Z, Chen H (2012) Cdbia: a dynamic community detection method based on incremental analysis. In: 2012 international conference on systems and informatics (ICSAI). IEEE, pp 2224–2228

    Chapter  Google Scholar 

  • Lu Z, Wen Y, Cao G (2013) Community detection in weighted networks: Algorithms and applications. In: 2013 I.E. international conference on pervasive computing and communications (PerCom). IEEE, pp 179–184

    Google Scholar 

  • Ngonmang B, Tchuente M, Viennet E (2012) Local community identification in social networks. Parallel Process Lett 22(01):1240,004

    Article  MathSciNet  MATH  Google Scholar 

  • Paevere P, Higgins A, Ren Z, Horn M, Grozev G, McNamara C (2014) Spatio-temporal modelling of electric vehicle charging demand and impacts on peak household electrical load. Sustain Sci 9(1):61–76

    Article  Google Scholar 

  • Rocha LE, Liljeros F, Holme P (2011) Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts. PLoS Comput Biol 7(3):e1001,109

    Article  Google Scholar 

  • Shang J, Liu L, Xie F, Chen Z, Miao J, Fang X, Wu C (2014) A real-time detecting algorithm for tracking community structure of dynamic networks. arXiv preprint arXiv:14072683

    Google Scholar 

  • Shi J, Malik J (2000) Normalized cuts and image segmentation. IEEE Trans Pattern Anal Mach Intell 22(8):888–905

    Article  Google Scholar 

  • Wang Y, Wu B, Du N (2008) Community evolution of social network: feature, algorithm and model. arXiv preprint arXiv:08044356

    Google Scholar 

  • Xie J, Szymanski BK (2012) Towards linear time overlapping community detection in social networks. In: Advances in knowledge discovery and data mining. Springer, Berlin, Heidelberg, pp 25–36

    Chapter  Google Scholar 

  • Xu KS, Kliger M, Hero AO III (2011) Tracking communities in dynamic social networks. In: Social computing, behavioral-cultural modeling and prediction. Springer, Berlin, Heidelberg, pp 219–226

    Chapter  Google Scholar 

  • Zeng X, Zhang Y (2013) Development of recurrent neural network considering temporal-spatial input dynamics for freeway travel time modeling. Comput Aided Civ Inf Eng 28(5):359–371

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ahmed Ould Mohamed Moctar .

Editor information

Editors and Affiliations

Section Editor information

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media LLC, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Moctar, A.O.M., Sarr, I. (2018). Instant Messaging for Detecting Dynamic Ego-Centered Communities. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-7131-2_110216

Download citation

Publish with us

Policies and ethics