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2016 | OriginalPaper | Chapter

Topy: Real-Time Story Tracking via Social Tags

Authors : Gevorg Poghosyan, M. Atif Qureshi, Georgiana Ifrim

Published in: Machine Learning and Knowledge Discovery in Databases

Publisher: Springer International Publishing

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Abstract

The Topy system automates real-time story tracking by utilizing crowd-sourced tagging on social media platforms. Topy employs a state-of-the-art Twitter hashtag recommender to continuously annotate news articles with hashtags, a rich meta-data source that allows connecting articles under drastically different timelines than typical keyword based story tracking systems. Employing social tags for story tracking has the following advantages: (1) social annotation of news enables the detection of emerging concepts and topic drift in a story; (2) hashtags go beyond topics by grouping articles based on connected themes (e.g., #rip, #blacklivesmatter, #icantbreath); (3) hashtags link articles that focus on subplots of the same story (e.g., #palmyra, #isis, #refugeecrisis).

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Literature
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Metadata
Title
Topy: Real-Time Story Tracking via Social Tags
Authors
Gevorg Poghosyan
M. Atif Qureshi
Georgiana Ifrim
Copyright Year
2016
DOI
https://doi.org/10.1007/978-3-319-46131-1_10

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