Multimedia Tools and Applications

, Volume 77, Issue 9, pp 11179–11201 | Cite as

User profiling for big social media data using standing ovation model

  • Muhammad Al-Qurishi
  • Saad Alhuzami
  • Majed AlRubaian
  • M. Shamim Hossain
  • Atif Alamri
  • Md. Abdur Rahman
Article
First Online:
Received:
Revised:
Accepted:

Abstract

Online Social Networks (OSNs) have recently been the subject of numerous studies that have attempted to develop effective methods for classifying and analyzing big content. Some of the key contributions of these studies to current scientific understanding include the identification of underlying topics within content (posts and messages), determination of each user’s influence and contributions, c) measurement of content quality, and extraction and analysis of users’ motives and preferences. We aimed to develop an integrative solution entailing a combination of these methodological advances within a single framework that could facilitate attribution and differentiate OSN members. Specifically, we examined peer effects within Twitter and assessed the propensity of members to alter their views on commonly discussed matters based on their exposure to alternative views expressed by respected and influential members. We availed of abundant available resources and tracked historical interactions of selected users to create a workable model that captured differences in opinions. The resulting solution enables peer influence within the online environment to be quantified and the level of investment of identified social media users in particular topics to be assessed.

Keywords

Data processing Big data mining Analysis of textual content Twitter 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

The authors are grateful to the Deanship of Scientific Research, King Saud University for funding through Vice Deanship of Scientific Research Chairs.

References

  1. 1.
    Abel F, Gao Q, Houben G-J, Tao K (2011) Semantic enrichment of twitter posts for user profile construction on the social web. In: Extended semantic web conference, pp 375–389Google Scholar
  2. 2.
    Alhamid, Mohammed F., Majdi Rawashdeh, Haiwei Dong, M. Anwar Hossain, and Abdulmotaleb El Saddik. Exploring latent preferences for context-aware personalized recommendation systems. IEEE Transactions on Human-Machine Systems 46(4):615–623Google Scholar
  3. 3.
    Al-Qurishi M, Aldrees R, AlRubaian M, Al-Rakhami M, Rahman SMM, Alamri A (2015) A new model for classifying social media users according to their behaviors. In: Web applications and networking (WSWAN), 2015 2nd world symposium on, pp 1–5Google Scholar
  4. 4.
    Benevenuto F, Rodrigues T, Cha M, Almeida V (2009) Characterizing user behavior in online social networks. In: Proceedings of the 9th ACM SIGCOMM conference on internet measurement conference, pp 49–62Google Scholar
  5. 5.
    Besel C, Schlötterer J, Granitzer M (2016) On the quality of semantic interest profiles for onine social network consumers. ACM SIGAPP Appl Comput Rev 16:5–14CrossRefGoogle Scholar
  6. 6.
    Besel C, Schlötterer J, Granitzer M (2016) Inferring semantic interest profiles from twitter followees: does twitter know better than your friends? In: Proceedings of the 31st Annual ACM symposium on applied computing pp 1152–1157Google Scholar
  7. 7.
    Chaudhary P et al (2016) XSS detection with automatic view isolation on online social network. Consumer electronics, 2016 I.E. 5th global conference on. IEEEGoogle Scholar
  8. 8.
    Chaudhary P et al (2017) A novel framework to alleviate dissemination of xss worms in online social network (osn) using view segregation. Neural Netw World 27(1):5CrossRefGoogle Scholar
  9. 9.
    Chen M, Zhang Y, Li Y, Mao S, Leung V (2015) EMC: emotion-aware mobile cloud computing in 5G. IEEE Netw 29(2):32–38CrossRefGoogle Scholar
  10. 10.
    Chen M, Ma Y, Hao Y, Li Y, Wu D, Zhang Y, Song E (2016) CP-robot: cloud-assisted pillow robot for emotion sensing and interaction. Industrialiot 2016, Guangzhou, ChinaGoogle Scholar
  11. 11.
    Chu Z, Gianvecchio S, Wang H, Jajodia S (2012) Detecting automation of twitter accounts: are you a human, bot, or cyborg? IEEE Trans Dependable Secure Comput 9:811–824CrossRefGoogle Scholar
  12. 12.
    Dougnon RY, Fournier-Viger P, Nkambou R (2015) Inferring user profiles in online social networks using a partial social graph. In: Canadian Conference on Artificial Intelligence, pp 84–99Google Scholar
  13. 13.
    Eason G, Noble B, Sneddon IN (1955) On certain integrals of Lipschitz-Hankel type involving products of Bessel functions. Philos Trans R Soc Lond A247:529–551 referencesMathSciNetCrossRefMATHGoogle Scholar
  14. 14.
    Fang Q, Xu C, Sang J, Hossain MS, Muhammad G (2015) Word-of-mouth understanding: entity-centric multimodal aspect-opinion mining in social media. IEEE Trans Multimed 17:2281–2296CrossRefGoogle Scholar
  15. 15.
    Fang Q, Sang J, Xu C, Shamim Hossain M (2015) Relational user attribute inference in social media. IEEE Trans Multimed 17(7):1031–1044CrossRefGoogle Scholar
  16. 16.
    Gupta BB, Agrawal DP (2016) Shingo Yamaguchi, "handbook of research on modern cryptographic solutions for computer and cyber security," IGI global. Publisher, USACrossRefGoogle Scholar
  17. 17.
    Hossain MS, El Saddik A (2008) A biologically-inspired multimedia content repurposing system in heterogeneous network environments. ACM/Springer Multimed Syst J 14(3):135–143CrossRefGoogle Scholar
  18. 18.
    Hossain MS, Muhammad G, Al Hamid MF, Song B (2016) Audio-visual emotion-aware big data recognition towards 5G. Mob Netw Appl 21(5):753–763CrossRefGoogle Scholar
  19. 19.
    Hossain MS, Alhamid MF, Muhammad G (2017) Collaborative analysis model for trending images on social networks. Futur Gener Comput SystGoogle Scholar
  20. 20.
    Java A, Song X, Finin T, Tseng B (2007) Why we twitter: understanding microblogging usage and communities. In: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on web mining and social network analysis, pp 56–65Google Scholar
  21. 21.
    Jiang J, Wilson C, Wang X, Sha W, Huang P, Dai Y et al (2013) Understanding latent interactions in online social networks. ACM Trans Web (TWEB) 7:18Google Scholar
  22. 22.
    Kwak H, Lee C, Park H, Moon S (2010) What is twitter, a social network or a news media? In: Proceedings of the 19th international conference on world wide web, pp 591–600Google Scholar
  23. 23.
    Li J, Yan H et al Location-sharing systems with enhanced privacy in mobile online social networks. IEEE Syst J.  https://doi.org/10.1109/JSYST.2015.2415835
  24. 24.
    Lo SL, Chiong R, Cornforth D (2016) Ranking of high-value social audiences on twitter. Decis Support Syst 85:34–48CrossRefGoogle Scholar
  25. 25.
    Miller JH, Page SE (2004) The standing ovation problem. Complexity 9:8–16CrossRefGoogle Scholar
  26. 26.
    Min W, Bao B-K, Xu C, Hossain MS (2015) Cross-platform multi-modal topic modeling for personalized inter-platform recommendation. IEEE Trans Multimed 17:1787–1801CrossRefGoogle Scholar
  27. 27.
    Peng, Min, Jiajia Huang, Hui Fu, Jiahui Zhu, Li Zhou, Yanxiang He, Fei Li (2013) High quality microblog extraction based on multiple features fusion and time-frequency transformation. In International Conference on Web Information Systems Engineering, pp. 188–201. Springer, Berlin, HeidelbergGoogle Scholar
  28. 28.
    Peng M, Gao B, Zhu J, Huang J, Yuan M, Li F (2016) High quality information extraction and query-oriented summarization for automatic query-reply in social network. Expert Systems with Applications 44:92–101Google Scholar
  29. 29.
    Pennacchiotti M, Popescu A-M (2011) Democrats, republicans and starbucks afficionados: user classification in twitter. In: Proceedings of the 17th ACM SIGKDD international conference on knowledge discovery and data mining, pp 430–438Google Scholar
  30. 30.
    Qian S, Zhang T, Xu C, Hossain MS (2015) Social event classification via boosted multimodal supervised latent dirichlet allocation. ACM Trans Multimed Comput Commun Appl (TOMM):11–27Google Scholar
  31. 31.
    Rawashdeh, Majdi, Mohammad Shorfuzzaman, Abdel Monim Artoli, M. Shamim Hossain, and Ahmed Ghoneim (2017) Mining tag-clouds to improve social media recommendation. Multimed Tools and Appl 76(20) 21157–21170Google Scholar
  32. 32.
    Riquelme F, González-Cantergiani P (2016) Measuring user influence on Twitter: A survey. Inf Process & Manag 52:949–975Google Scholar
  33. 33.
    Song J, Zhang Y, Duan K, Hossain MS, Rahman SMM (2016) TOLA: topic-oriented learning assistance based on cyber-physical system and big data. Futur Gener Comput Syst 75(2017):200–205Google Scholar
  34. 34.
    Tao, Ke, Fabian Abel, Qi Gao, and Geert-Jan Houben. "TUMS: twitter-based user modeling service." In Extended Semantic Web Conference, pp. 269–283. Springer, Berlin, Heidelberg, 2011Google Scholar
  35. 35.
    Vosecky, Jan, Kenneth Wai-Ting Leung, Wilfred Ng (2012) Searching for Quality Microblog Posts: Filtering and Ranking Based on Content Analysis and Implicit Links. In DASFAA 1:397–413Google Scholar
  36. 36.
    Yang T, Lee D, Yan S (2013) Steeler nation, 12th man, and boo birds: classifying twitter user interests using time series. In: Advances in social networks analysis and mining (ASONAM), 2013 IEEE/ACM international conference on, pp 684–691Google Scholar
  37. 37.
    Yang Z, Wilson C, Wang X, Gao T, Zhao BY, Dai Y (2014) Uncovering social network sybils in the wild. ACM Trans Knowl Discov Data (TKDD) 8:2Google Scholar
  38. 38.
    Yang X et al (2015) Automatic visual concept learning for social event understanding. IEEE Trans Multimed 17(3):346–358CrossRefGoogle Scholar
  39. 39.
    Zhang Z et al (2016) CyVOD: a novel trinity multimedia social network scheme (MTAP-D-16-01532). MTAP. Springer, New YorkGoogle Scholar
  40. 40.
    Zhang Z et al (2016) Social media security and trustworthiness: overview and new direction. Futur Gener Comput Syst 2016Google Scholar
  41. 41.
    Zuber M (2014) A survey of data mining techniques for social network analysis. Int J Res Comput Eng Electron 3(6):1–8Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Muhammad Al-Qurishi
    • 1
  • Saad Alhuzami
    • 1
  • Majed AlRubaian
    • 1
  • M. Shamim Hossain
    • 1
    • 2
  • Atif Alamri
    • 1
    • 2
  • Md. Abdur Rahman
    • 3
  1. 1.Chair of Pervasive and Mobile Computing, Collage of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia
  2. 2.Department of Software Engineering, College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia
  3. 3.Department of Computer ScienceUniversity of Prince Muqrin Madinah al munawarahSaudi Arabia

Personalised recommendations