• Bansal S, Kumar M, Raghaw C and Kumar N. (2024). Sentiment and hashtag-aware attentive deep neural network for multimodal post popularity prediction. Neural Computing and Applications. 10.1007/s00521-024-10755-5. 37:4. (2799-2824). Online publication date: 1-Feb-2025.

    https://link.springer.com/10.1007/s00521-024-10755-5

  • Wang Z, Wang X, Xiong F and Chen H. (2024). A Survey of Deep Learning-Based Information Cascade Prediction. Symmetry. 10.3390/sym16111436. 16:11. (1436).

    https://www.mdpi.com/2073-8994/16/11/1436

  • Cheng Z, Zhang J, Xu X, Trajcevski G, Zhong T and Zhou F. Retrieval-Augmented Hypergraph for Multimodal Social Media Popularity Prediction. Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. (445-455).

    https://doi.org/10.1145/3637528.3672041

  • Viswanatha Reddy G, Chaitanya B, Prathyush P, Sumanth M, Mrinalini C, Dileep Kumar P and Mukherjee S. (2023). DFW-PP: dynamic feature weighting-based popularity prediction for social media content. The Journal of Supercomputing. 10.1007/s11227-023-05672-8. 80:4. (5708-5730). Online publication date: 1-Mar-2024.

    https://link.springer.com/10.1007/s11227-023-05672-8

  • Zavrak S and Yilmaz S. (2023). Email spam detection using hierarchical attention hybrid deep learning method. Expert Systems with Applications: An International Journal. 233:C. Online publication date: 15-Dec-2023.

    https://doi.org/10.1016/j.eswa.2023.120977

  • Ji L, Park C, Rao Z and Chen Q. Neural Image Popularity Assessment with Retrieval-augmented Transformer. Proceedings of the 31st ACM International Conference on Multimedia. (2427-2436).

    https://doi.org/10.1145/3581783.3611918

  • Zhang R, Huang T, Wu C and Sun L. (2023). Who is the Rising Star? Demystifying the Promising Streamers in Crowdsourced Live Streaming IEEE INFOCOM 2023 - IEEE Conference on Computer Communications. 10.1109/INFOCOM53939.2023.10228881. 979-8-3503-3414-2. (1-10).

    https://ieeexplore.ieee.org/document/10228881/

  • Wang J, Yang S, Zhao H and Yang Y. (2023). Social media popularity prediction with multimodal hierarchical fusion model. Computer Speech & Language. 10.1016/j.csl.2023.101490. 80. (101490). Online publication date: 1-May-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S0885230823000098

  • Xu X, Zhou F, Zhang K, Liu S and Trajcevski G. CasFlow: Exploring Hierarchical Structures and Propagation Uncertainty for Cascade Prediction. IEEE Transactions on Knowledge and Data Engineering. 10.1109/TKDE.2021.3126475. 35:4. (3484-3499).

    https://ieeexplore.ieee.org/document/9611000/

  • Zhong C, Xiong F, Pan S, Wang L and Xiong X. (2023). Hierarchical attention neural network for information cascade prediction. Information Sciences. 10.1016/j.ins.2022.11.163. 622. (1109-1127). Online publication date: 1-Apr-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S0020025522014876

  • Wang G, Ma J and Chen G. (2023). Attentive statement fraud detection. Decision Support Systems. 167:C. Online publication date: 1-Apr-2023.

    https://doi.org/10.1016/j.dss.2022.113913

  • Liu A, Wang X, Xu N, Liu J, Su Y, Zhang Q, Zhang S, Tang Y, Guo J, Jin G and Li X. (2023). SMPC: boosting social media popularity prediction with caption. Multimedia Systems. 10.1007/s00530-022-01030-5. 29:2. (577-586). Online publication date: 1-Apr-2023.

    https://link.springer.com/10.1007/s00530-022-01030-5

  • Sarkar S, Basu S, Paul A and Prasad Mukherjee D. ViViD: View Prediction of Online Video Through Deep Neural Network-Based Analysis of Subjective Video Attributes. IEEE Transactions on Broadcasting. 10.1109/TBC.2022.3231100. 69:1. (191-200).

    https://ieeexplore.ieee.org/document/10012278/

  • Huang S and Yu W. (2023). Cascade Prediction with Recurrent Neural Networks and Diffusion Depth Distributions 2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE). 10.1109/NNICE58320.2023.10105676. 979-8-3503-3597-2. (70-77).

    https://ieeexplore.ieee.org/document/10105676/

  • Li H, Xia C, Wang T, Wen S, Chen C and Xiang Y. (2021). Capturing Dynamics of Information Diffusion in SNS: A Survey of Methodology and Techniques. ACM Computing Surveys. 55:1. (1-51). Online publication date: 31-Jan-2023.

    https://doi.org/10.1145/3485273

  • Xie J, Zhu Y and Chen Z. Micro-Video Popularity Prediction Via Multimodal Variational Information Bottleneck. IEEE Transactions on Multimedia. 10.1109/TMM.2021.3120537. 25. (24-37).

    https://ieeexplore.ieee.org/document/9576573/

  • Li H, Qian Y, Jiang Y, Liu Y and Zhou F. (2023). A novel label-based multimodal topic model for social media analysis. Decision Support Systems. 164:C. Online publication date: 1-Jan-2023.

    https://doi.org/10.1016/j.dss.2022.113863

  • Liu P, Yu Z, Sun Y and Xi M. (2023). Video Popularity Prediction Based on Knowledge Graph and LSTM Network. Data Science. 10.1007/978-981-99-5968-6_32. (455-474).

    https://link.springer.com/10.1007/978-981-99-5968-6_32

  • Liu J, Zhang X, Alo R, Huang X, Cheng L and Deng F. (2022). CrossCas: A Novel Cross-Platform Approach for Predicting Cascades in Online Social Networks with Hidden Markov Model GLOBECOM 2022 - 2022 IEEE Global Communications Conference. 10.1109/GLOBECOM48099.2022.10001560. 978-1-6654-3540-6. (6415-6420).

    https://ieeexplore.ieee.org/document/10001560/

  • Zhang P, Liu B, Lu T, Ding X, Gu H and Gu N. (2022). Jointly Predicting Future Content in Multiple Social Media Sites Based on Multi-task Learning. ACM Transactions on Information Systems. 40:4. (1-28). Online publication date: 31-Oct-2022.

    https://doi.org/10.1145/3495530

  • Zhao Y, Wang Z and Lam E. (2022). Improving Source Localization by Perturbing Graph Diffusion 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA). 10.1109/DSAA54385.2022.10032349. 978-1-6654-7330-9. (1-9).

    https://ieeexplore.ieee.org/document/10032349/

  • Zhang Z, Yin Z, Wen J, Sun L, Su S and Yu P. DeepBlue: Bi-Layered LSTM for Tweet popUlarity Estimation. IEEE Transactions on Knowledge and Data Engineering. 10.1109/TKDE.2021.3049529. 34:10. (4737-4752).

    https://ieeexplore.ieee.org/document/9314897/

  • Mudgal P and Liu F. (2022). Are High-quality Photos More Popular Than Low-quality Ones? A Quantitative Study 2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP). 10.1109/MMSP55362.2022.9948731. 978-1-6654-7189-3. (1-5).

    https://ieeexplore.ieee.org/document/9948731/

  • Unal M, Kovashka A, Chung W and Lin Y. Visual Persuasion in COVID-19 Social Media Content: A Multi-Modal Characterization. Companion Proceedings of the Web Conference 2022. (694-704).

    https://doi.org/10.1145/3487553.3524647

  • Wang J, Jiang J and Zhao L. An Invertible Graph Diffusion Neural Network for Source Localization. Proceedings of the ACM Web Conference 2022. (1058-1069).

    https://doi.org/10.1145/3485447.3512155

  • Tang S, Li Q, Ma X, Gao C, Wang D, Jiang Y, Ma Q, Zhang A and Chen H. Knowledge-based Temporal Fusion Network for Interpretable Online Video Popularity Prediction. Proceedings of the ACM Web Conference 2022. (2879-2887).

    https://doi.org/10.1145/3485447.3511934

  • Zhou F, Xu X, Trajcevski G and Zhang K. (2021). A Survey of Information Cascade Analysis. ACM Computing Surveys. 54:2. (1-36). Online publication date: 31-Mar-2022.

    https://doi.org/10.1145/3433000

  • Zheng Z, Gao X, Ma X and Chen G. Predicting Hot Events in the Early Period through Bayesian Model for Social Networks. IEEE Transactions on Knowledge and Data Engineering. 10.1109/TKDE.2020.2994946. 34:3. (1390-1403).

    https://ieeexplore.ieee.org/document/9094319/

  • Zhao L, Zhang L and Jiang J. (2021). Hot question prediction in Stack Overflow. IET Software. 10.1049/sfw2.12013. 15:1. (90-106). Online publication date: 1-Feb-2021.

    https://onlinelibrary.wiley.com/doi/10.1049/sfw2.12013

  • Wang J, Wu Y and Wang L. (2021). Predicting Implicit User Preferences with Multimodal Feature Fusion for Similar User Recommendation in Social Media. Applied Sciences. 10.3390/app11031064. 11:3. (1064).

    https://www.mdpi.com/2076-3417/11/3/1064

  • Yang J, Men Y and Zhao Y. (2020). Will people like your illustration? Popularity assessment of illustrations. Electronics Letters. 10.1049/ell2.12054. 57:2. (58-61). Online publication date: 1-Jan-2021.

    https://onlinelibrary.wiley.com/doi/10.1049/ell2.12054

  • Yu H, Liang M, Xie R, Sun Z, Zhang B and Lin L. (2021). MMNet: Multi-granularity Multi-mode Network for Item-Level Share Rate Prediction. Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track. 10.1007/978-3-030-86517-7_13. (201-217).

    https://link.springer.com/10.1007/978-3-030-86517-7_13

  • Gao L, Zhou B, Jia Y, Tu H and Wang Y. (2021). Information Cascading in Social Networks. MDATA: A New Knowledge Representation Model. 10.1007/978-3-030-71590-8_14. (234-254).

    http://link.springer.com/10.1007/978-3-030-71590-8_14

  • Liu Y, Bao Z, Zhang Z, Tang D and Xiong F. (2020). Information cascades prediction with attention neural network. Human-centric Computing and Information Sciences. 10.1186/s13673-020-00218-w. 10:1. Online publication date: 1-Dec-2020.

    https://hcis-journal.springeropen.com/articles/10.1186/s13673-020-00218-w

  • Yang L, Guo X, Wang H and Chen W. (2020). A Video Popularity Prediction Scheme with Attention-Based LSTM and Feature Embedding GLOBECOM 2020 - 2020 IEEE Global Communications Conference. 10.1109/GLOBECOM42002.2020.9322267. 978-1-7281-8298-8. (1-6).

    https://ieeexplore.ieee.org/document/9322267/

  • Li Y, Chai Y, Yin H and Chen B. (2020). A novel feature learning framework for high-dimensional data classification. International Journal of Machine Learning and Cybernetics. 10.1007/s13042-020-01188-2.

    http://link.springer.com/10.1007/s13042-020-01188-2

  • Lai X, Zhang Y and Zhang W. HyFea: Winning Solution to Social Media Popularity Prediction for Multimedia Grand Challenge 2020. Proceedings of the 28th ACM International Conference on Multimedia. (4565-4569).

    https://doi.org/10.1145/3394171.3416273

  • Liu S, Xie J, Zou C and Chen Z. (2020). User Conditional Hashtag Recommendation for Micro-Videos 2020 IEEE International Conference on Multimedia and Expo (ICME). 10.1109/ICME46284.2020.9102824. 978-1-7281-1331-9. (1-6).

    https://ieeexplore.ieee.org/document/9102824/

  • Gao L, Zhou B, Jia Y, Tu H, Wang Y, Chen C, Wang H and Zhuang H. (2020). Deep Learning for Social Network Information Cascade Analysis: a survey 2020 IEEE Fifth International Conference on Data Science in Cyberspace (DSC). 10.1109/DSC50466.2020.00022. 978-1-7281-9558-2. (89-97).

    https://ieeexplore.ieee.org/document/9172878/

  • Wang L, Liu R and Vosoughi S. Salienteye: Maximizing Engagement While Maintaining Artistic Style on Instagram Using Deep Neural Networks. Proceedings of the 2020 International Conference on Multimedia Retrieval. (331-335).

    https://doi.org/10.1145/3372278.3390736

  • Wang X, Zhang Y and Yamasaki T. Earn More Social Attention: User Popularity Based Tag Recommendation System. Companion Proceedings of the Web Conference 2020. (212-216).

    https://doi.org/10.1145/3366424.3383543

  • Cao Q, Shen H, Gao J, Wei B and Cheng X. Popularity Prediction on Social Platforms with Coupled Graph Neural Networks. Proceedings of the 13th International Conference on Web Search and Data Mining. (70-78).

    https://doi.org/10.1145/3336191.3371834

  • Yu H, Hu Y and Shi P. A Prediction Method of Peak Time Popularity Based on Twitter Hashtags. IEEE Access. 10.1109/ACCESS.2020.2983583. 8. (61453-61461).

    https://ieeexplore.ieee.org/document/9047849/

  • Chen Z, Xu K and Zhang W. Content-Based Video Relevance Prediction with Multi-view Multi-level Deep Interest Network. Proceedings of the 27th ACM International Conference on Multimedia. (2607-2611).

    https://doi.org/10.1145/3343031.3356068

  • Ding K, Wang R and Wang S. Social Media Popularity Prediction. Proceedings of the 27th ACM International Conference on Multimedia. (2682-2686).

    https://doi.org/10.1145/3343031.3356062

  • Ding K, Ma K and Wang S. Intrinsic Image Popularity Assessment. Proceedings of the 27th ACM International Conference on Multimedia. (1979-1987).

    https://doi.org/10.1145/3343031.3351007

  • Wang X, Zhang Y and Yamasaki T. User-Aware Folk Popularity Rank. Proceedings of the 27th ACM International Conference on Multimedia. (1970-1978).

    https://doi.org/10.1145/3343031.3350920

  • Liu S, Chen Z, Liu H and Hu X. User-Video Co-Attention Network for Personalized Micro-video Recommendation. The World Wide Web Conference. (3020-3026).

    https://doi.org/10.1145/3308558.3313513

  • Liu N, Lu P, Zhang W and Wang J. (2019). Knowledge-Aware Deep Dual Networks for Text-Based Mortality Prediction 2019 IEEE 35th International Conference on Data Engineering (ICDE). 10.1109/ICDE.2019.00127. 978-1-5386-7474-1. (1406-1417).

    https://ieeexplore.ieee.org/document/8731459/

  • Wu H, Zhang W, Shen W and Wang J. Hybrid Deep Sequential Modeling for Social Text-Driven Stock Prediction. Proceedings of the 27th ACM International Conference on Information and Knowledge Management. (1627-1630).

    https://doi.org/10.1145/3269206.3269290

  • Feng Y, Wu Z and Wu H. A convolutional sequential model for network load forecasting. Proceedings of the 10th International Conference on Internet Multimedia Computing and Service. (1-6).

    https://doi.org/10.1145/3240876.3240897

  • Lu P, Ji L, Zhang W, Duan N, Zhou M and Wang J. R-VQA. Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. (1880-1889).

    https://doi.org/10.1145/3219819.3220036

  • Wang W, Zhang W, Wang J, Yan J and Zha H. Learning sequential correlation for user generated textual content popularity prediction. Proceedings of the 27th International Joint Conference on Artificial Intelligence. (1625-1631).

    /doi/10.5555/3304415.3304646

  • Bielski A and Trzcinski T. Understanding Multimodal Popularity Prediction of Social Media Videos With Self-Attention. IEEE Access. 10.1109/ACCESS.2018.2884831. 6. (74277-74287).

    https://ieeexplore.ieee.org/document/8558491/

  • Wang W, Zhang W and Wang J. (2018). Factorization Meets Memory Network: Learning to Predict Activity Popularity. Database Systems for Advanced Applications. 10.1007/978-3-319-91458-9_31. (509-525).

    https://link.springer.com/10.1007/978-3-319-91458-9_31

  • Wang L, Zhang W, He X and Zha H. (2018). Personalized Prescription for Comorbidity. Database Systems for Advanced Applications. 10.1007/978-3-319-91458-9_1. (3-19).

    http://link.springer.com/10.1007/978-3-319-91458-9_1