1 |
C. C. Aggarwal, Social Network Data Analytics. Boston, MA: Springer, 2011.
|
2 |
L. Berkani, S. Belkacem, M. Ouafi, and A. Guessoum, "Recommendation of users in social networks: A semantic and social based classification approach," Expert Systems, article no. e12634, 2020. https://doi.org/10.1111/exsy.12634
DOI
|
3 |
C. C. Aggarwal and K. Subbian, "Event detection in social streams," in Proceedings of the 2012 SIAM International Conference On Data Mining, Anaheim, CA, 2012, pp. 624-635.
|
4 |
C. Li, W. K. Cheung, Y. Ye, X. Zhang, D. Chu, and X. Li, "The author-topic-community model for author interest profiling and community discovery," Knowledge and Information Systems, vol. 44, no. 2, pp. 359- 383, 2015.
DOI
|
5 |
D. Zhou, I. Councill, H. Zha, and C. L. Giles, "Discovering temporal communities from social network documents," in Proceedings of the 7th IEEE International Conference on Data Mining (ICDM), Omaha, NE, 2007, pp. 745-750.
|
6 |
N. Pathak, C. DeLong, K.Erickson, and A. Banerjee, "Social topic models for community extraction," Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, 2008.
|
7 |
X. Wang, N. Mohanty, and A. McCallum, "Group and topic discovery from relations and their attributes," Advances in Neural Information Processing Systems, vol. 18, pp. 1449-1456, 2006.
|
8 |
H. H. Kim and H. Y. Rhee, "An ontology-based labeling of influential topics using topic network analysis," Journal of Information Processing Systems, vol. 15, no. 5, pp. 1096-1107, 2019.
DOI
|
9 |
A. Beykikhoshk, O. Arandjelovic, D. Phung, and S. Venkatesh, "Discovering topic structures of a temporally evolving document corpus," Knowledge and Information Systems, vol. 55, no. 3, pp. 599-632, 2018.
DOI
|
10 |
L. C. Freeman, "Visualizing social networks," Journal of Social Structure, 2000 [Online]. Available: https://www.cmu.edu/joss/content/articles/volume1/Freeman.html.
|
11 |
Z. Yin, L. Cao, Q. Gu, and J. Han, "Latent community topic analysis: Integration of community discovery with topic modeling," ACM Transactions on Intelligent Systems and Technology (TIST), vol. 3, no. 4, pp. 1-21, 2012.
|
12 |
T. Ho and P. Do, "Analyzing the changes in online community based on topic model and self-organizing map," International Journal of Advanced Computer Science and Applications (IJACSA), vol. 6, no. 7, pp. 100-108, 2015.
|
13 |
D. M. Sharma and M. M. Baig, "Sentiment analysis on social networking: a literature review," 2015 [Online]. Available from: https://www.researchgate.net/profile/Durgesh_Sharma8/publication/325120893_Using_Data_Mining_For_Prediction_A_Conceptual_Analysis/links/5ef35b3d92851c35353ba7c4/Using-Data-MiningFor-Prediction-A-Conceptual-Analysis.pdf.
|
14 |
X. Wang, N. Mohanty, and A. McCallum, "Group and topic discovery from relations and their attributes," Advances in Neural Information Processing Systems, vol. 18, pp. 1449-1456, 2006.
|
15 |
H. Fani, F. Zarrinkalam, X. Zhao, Y. Feng, E. Bagheri, and W. Du, "Temporal identification of latent communities on Twitter," 2015 [Online]. Available: https://arxiv.org/abs/1509.04227.
|
16 |
J. Singh and A. K. Singh, "NSLPCD: topic based tweets clustering using node significance based label propagation community detection algorithm," Annals of Mathematics and Artificial Intelligence, 2020. https://doi.org/10.1007/s10472-020-09709-z
DOI
|
17 |
M. Steyvers, P. Smyth, M. Rosen-Zvi, and T. Griffiths, "Probabilistic author-topic models for information discovery," in Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, WA, 2004, pp. 306-315.
|
18 |
T. Yang, Y. Chi, S. Zhu, Y. Gong, and R. Jin, "Detecting communities and their evolutions in dynamic social networks: a Bayesian approach," Machine Learning, vol. 82, no. 2, pp. 157-189, 2011.
DOI
|
19 |
T. Griffiths, "Gibbs sampling in the generative model of latent Dirichlet allocation," 2002 [Online]. Available: https://people.cs.umass.edu/-wallach/courses/s11/cmpsci791ss/readings/griffiths02gibbs.pdf.
|
20 |
T. Ho and P. Do, "Social network analysis based on topic model with temporal factor," International Journal of Knowledge and Systems Science (IJKSS), vol. 9, no. 1, pp. 82-97, 2018.
DOI
|
21 |
H. A. Abdelbary, A. M. ElKorany, and R. Bahgat, "Utilizing deep learning for content-based community detection," in Proceedings of 2014 Science and Information Conference, London, UK, 2014, pp. 777-784.
|
22 |
T. Kohonen, "Self-organized formation of topologically correct feature maps," Biological Cybernetics, vol. 43, no. 1, pp. 59-69, 1982.
DOI
|
23 |
S. Haykin, Neural Networks: A Comprehensive Foundation, 2nd ed. Upper Saddle River, NJ: Prentice-Hall, 1999. pp. 443-465.
|
24 |
Kohonen T, "Self-Organization and Associative Memory", Springer, Berlin, 1984.
|
25 |
C. Brew and S. S. im Walde, "Spectral clustering for German verbs," in Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP), Philadelphia, PA, 2002, pp. 117-124.
|
26 |
T. Joachims, "Transductive inference for text classification using support vector machines," in Proceedings of the 16th International Conference on Machine Learning (ICML), Bled, Slovenia, 1999, pp. 200-209.
|
27 |
M. Halkidi, Y. Batistakis, and M. Vazirgiannis, "Cluster validity methods: part I," ACM SIGMOD Record, vol. 31, no. 2, pp. 40-45, 2002.
DOI
|
28 |
M. Halkidi, Y. Batistakis, and M. Vazirgiannis, "Clustering validity checking methods: Part II," ACM SIGMOD Record, vol. 31, no. 3, pp. 19-27, 2002.
DOI
|
29 |
T. Fawcett, "An introduction to ROC analysis," Pattern Recognition Letters, vol. 27, no. 8, pp. 861-874, 2006.
DOI
|