Probabilistic Model of Narratives Over Topical Trends in Social Media: A Discrete Time Model
A probabilistic discrete-time topic model and extractive framework for identifying topical trends and narrative summaries in timestamped social-media data.- doi
- 10.1145/3372923.3404790
- name
- Probabilistic Model of Narratives Over Topical Trends in Social Media: A Discrete Time Model
- pages
- 10
- acm_url
- https://dl.acm.org/doi/10.1145/3372923.3404790
- authors
- Toktam A. Oghaz, Ece Çiğdem Mutlu, Jasser Jasser, Niloofar Yousefi, Ivan Garibay
- doi_url
- https://doi.org/10.1145/3372923.3404790
- license
- restricted
- summary
- A probabilistic discrete-time topic model and extractive framework for identifying topical trends and narrative summaries in timestamped social-media data.
- keywords
- Topic Modeling; Graphical Models; Narrative Extraction; Topic Detection and Tracking; Extractive Text Summarization; Online Social Media
- source_pdf
- HT-2020_51-35_3372923/3372923.3404790.pdf
- import_kind
- full_text
- open_access
- false
- ccs_concepts
- Information systems → Data mining; Computing methodologies → Information extraction; Topic modeling; Mathematics of computing → Gibbs sampling; Networks → Online social networks
- displayAuthor
- Toktam A. Oghaz, Ece Çiğdem Mutlu, Jasser Jasser, Niloofar Yousefi, Ivan Garibay
- source_attribution
- Formatting converted from the ACM version of record under supplied ACM publication authorization.
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