Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Optimizing the Efficiency, Vulnerability and Robustness of Road-Based Para-Transit Networks Using Genetic Algorithm Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Retweet Prediction Using Social-Aware Probabilistic Matrix Factorization

Authors : Bo Jiang, Zhigang Lu, Ning Li, Jianjun Wu, Zhengwei Jiang

Published in: Computational Science – ICCS 2018

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Retweet prediction is a fundamental and crucial task in social networking websites as it may influence the process of information diffusion. Existing prediction approaches simply ignore social contextual information or don’t take full advantage of these potential factors, damaging the performance of prediction. Besides, the sparsity of retweet data also severely disturb the performance of these models. In this paper, we propose a novel retweet prediction model based on probabilistic matrix factorization method by integrating the observed retweet data, social influence and message semantic to improve the accuracy of prediction. Finally, we incorporate these social contextual regularization terms into the objective function. Comprehensive experiments on the real-world dataset clearly validate both the effectiveness and efficiency of our model compared with several state-of the-art baselines.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter A Conceptual Framework for Social Movements Analytics for National Security
next chapter Cascading Failure Based on Load Redistribution of a Smart Grid with Different Coupling Modes
Literature
1.
Abdullah, N.A., Nishioka, D., Tanaka, Y., Murayama, Y.: User’s action and decision making of retweet messages towards reducing misinformation spread during disaster. J. Inf. Process. 23(1), 31–40 (2015)
2.
Can, E.F., Oktay, H., Manmatha, R.: Predicting retweet count using visual cues. In: CIKM, pp. 1481–1484. ACM (2013)
3.
Chen, J., Liu, Y., Zou, M.: User emotion for modeling retweeting behaviors. Neural Netw. 96, 11–21 (2017)CrossRef
4.
Guo, G., Zhang, J., Yorke-Smith, N.: TrustSVD: collaborative filtering with both the explicit and implicit influence of user trust and of item ratings. In: AAAI, pp. 123–129 (2015)
5.
Li, C., Wang, H., Zhang, Z., Sun, A., Ma, Z.: Topic modeling for short texts with auxiliary word embeddings. In: SIGIR, pp. 165–174. ACM (2016)
6.
Liu, L., Tang, J., Han, J., Jiang, M., Yang, S.: Mining topic-level influence in heterogeneous networks. In: CIKM, pp. 199–208. ACM (2010)
7.
Luo, Z., Osborne, M., Tang, J., Wang, T.: Who will retweet me?: finding retweeters in twitter. In: SIGIR, pp. 869–872. ACM (2013)
8.
Ma, H., King, I., Lyu, M.R.: Learning to recommend with social trust ensemble. In: SIGIR, pp. 203–210 (2009)
9.
Ma, H., Yang, H., Lyu, M.R., King, I.: SoRec: social recommendation using probabilistic matrix factorization. In: CIKM, pp. 931–940 (2008)
10.
Metaxas, P.T., Mustafaraj, E., Wong, K., Zeng, L., O’Keefe, M., Finn, S.: What do retweets indicate? Results from user survey and meta-review of research. In: ICWSM, pp. 658–661 (2015)
11.
Peng, H.-K., Zhu, J., Piao, D., Yan, R., Zhang, Y.: Retweet modeling using conditional random fields. In: ICDM, pp. 336–343. IEEE (2011)
12.
Salakhutdinov, R., Mnih, A.: Probabilistic matrix factorization. In: NIPS, pp. 1257–1264 (2007)
13.
Suh, B., Hong, L., Pirolli, P., Chi, E.H.: Want to be retweeted? Large scale analytics on factors impacting retweet in twitter network. In: SocialCom, pp. 177–184. IEEE (2010)
14.
Tang, J., Wang, S., Hu, X., Yin, D., Bi, Y., Chang, Y., Liu, H.: Recommendation with social dimensions. In: AAAI, pp. 251–257 (2016)
15.
Wang, C., Li, Q., Wang, L., Zeng, D.D.: Incorporating message embedding into co-factor matrix factorization for retweeting prediction. In: IJCNN, pp. 1265–1272. IEEE (2017)
16.
Wang, M., Zuo, W., Wang, Y.: A multidimensional nonnegative matrix factorization model for retweeting behavior prediction. Math. Probl. Eng. 2015, 1–10 (2015)
17.
Yang, B., Lei, Y., Liu, J., Li, W.: Social collaborative filtering by trust. In: IJCAI, pp. 2747–2753 (2013)
18.
Zhang, J., Tang, J., Li, J., Liu, Y., Xing, C.: Who influenced you? Predicting retweet via social influence locality. ACM TKDD 9(3), 25 (2015)
19.
Zhang, Q., Gong, Y., Guo, Y., Huang, X.: Retweet behavior prediction using hierarchical dirichlet process. In: AAAI, pp. 403–409 (2015)
20.
Zhao, T., McAuley, J., King, I.: Leveraging social connections to improve personalized ranking for collaborative filtering. In: CIKM, pp. 261–270. ACM (2014)
Metadata
Title
Retweet Prediction Using Social-Aware Probabilistic Matrix Factorization
Authors
Bo Jiang
Zhigang Lu
Ning Li
Jianjun Wu
Zhengwei Jiang
Copyright Year
2018
Book
Computational Science – ICCS 2018

Print ISBN: 978-3-319-93697-0

Electronic ISBN: 978-3-319-93698-7

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-93698-7_24

Premium Partner

    Image Credits