POPULARITY PREDICTION OF 9GAG POSTS WITH USAGE OF MULTIMODAL DATA AND FOCUS ON TEXTUAL DATA
DOI:
https://doi.org/10.24867/16BE38IlicKeywords:
Sentiment analysis, text mining, popularity predictionAbstract
Popularity prediction of 9gag posts could help recognize and analyze key elements of popular content on social media. This type of research could be necessary for areas such as marketing. This paper presents the system's architecture for 9gag post popularity prediction, where the focus is on analyzing the textual elements of the posts. Two approaches were used - training multiple different classifiers and classifier staking. Results are presented and analyzed at the end, and future work of the system is discussed.
References
[1] 9gag - https://9gag.com/
[2] MEGHAWAT, Mayank, et al. A multimodal approach to predict social media popularity. In: 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2018. p. 190-195.
[3] SMP-T1 in ACM Multimedia Grand Challenge. https://social-media-prediction.github.io/MM17PredictionChallenge/leaderboard.html, 2017
[4] MAZLOOM, Masoud, et al. Multimodal popularity prediction of brand-related social media posts. In: Proceedings of the 24th ACM international conference on Multimedia. 2016. p. 197-201.
[5] Stanford Core NLP - https://stanfordnlp.github.io/CoreNLP/
[6] TERENTIEV, Andrei; TEMPEST, Alanna. Predicting Reddit Post Popularity Via Initial Commentary. nd): n. pag, 2014.
[7] Kitayama, Kotaro et al. “Popularity Prediction of Online Petitions using a Multimodal DeepRegression Model.” ALTA (2020).
[8] DEVLIN, Jacob, et al. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805, 2018.
[2] MEGHAWAT, Mayank, et al. A multimodal approach to predict social media popularity. In: 2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR). IEEE, 2018. p. 190-195.
[3] SMP-T1 in ACM Multimedia Grand Challenge. https://social-media-prediction.github.io/MM17PredictionChallenge/leaderboard.html, 2017
[4] MAZLOOM, Masoud, et al. Multimodal popularity prediction of brand-related social media posts. In: Proceedings of the 24th ACM international conference on Multimedia. 2016. p. 197-201.
[5] Stanford Core NLP - https://stanfordnlp.github.io/CoreNLP/
[6] TERENTIEV, Andrei; TEMPEST, Alanna. Predicting Reddit Post Popularity Via Initial Commentary. nd): n. pag, 2014.
[7] Kitayama, Kotaro et al. “Popularity Prediction of Online Petitions using a Multimodal DeepRegression Model.” ALTA (2020).
[8] DEVLIN, Jacob, et al. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805, 2018.
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Published
2022-02-04
Issue
Section
Electrotechnical and Computer Engineering
