Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Svetlana S. Bodrunova & Andrey V. Orekhov & Ivan S. Blekanov & Nikolay S. Lyudkevich & Nikita A. Tarasov, 2020. "Topic Detection Based on Sentence Embeddings and Agglomerative Clustering with Markov Moment," Future Internet, MDPI, vol. 12(9), pages 1-17, August.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Svetlana S. Bodrunova, 2022. "Editorial for the Special Issue “Selected Papers from the 9th Annual Conference ‘Comparative Media Studies in Today’s World’ (CMSTW’2021)”," Future Internet, MDPI, vol. 14(11), pages 1-3, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Svetlana S. Bodrunova, 2022. "Editorial for the Special Issue “Selected Papers from the 9th Annual Conference ‘Comparative Media Studies in Today’s World’ (CMSTW’2021)”," Future Internet, MDPI, vol. 14(11), pages 1-3, November.
- Andrey V. Orekhov, 2021. "Quasi-Deterministic Processes with Monotonic Trajectories and Unsupervised Machine Learning," Mathematics, MDPI, vol. 9(18), pages 1-26, September.
- Ivan Blekanov & Svetlana S. Bodrunova & Askar Akhmetov, 2021. "Detection of Hidden Communities in Twitter Discussions of Varying Volumes," Future Internet, MDPI, vol. 13(11), pages 1-17, November.
More about this item
Keywords
natural language processing; deep learning models; transformer models; abstractive summarization; social networks; opinion mining; Reddit; Twitter; pool summarization;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:14:y:2022:i:3:p:69-:d:756534. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.