Topy: Real-time Story Tracking via Social Tags

Files in This Item:
File Description SizeFormat 
insight_publication.pdf592.14 kBAdobe PDFDownload
Title: Topy: Real-time Story Tracking via Social Tags
Authors: Poghosyan, Gevorg
Qureshi, M. Atif
Ifrim, Georgiana
Permanent link: http://hdl.handle.net/10197/7832
Date: 23-Sep-2016
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).
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Publisher: Springer
Copyright (published version): 2016 Springer
Keywords: Machine learningStatisticsStory trackingNewsSocial mediaSocial tags
DOI: 10.1007/978-3-319-46131-1_10
Language: en
Status of Item: Peer reviewed
Is part of: Berendt, B., Bringmann, B., Fromont, E., Garriga, G., Miettinen, P., Tatti, N. and Tresp, V. (eds.). Proceedings Part 3: Machine Learning and Knowledge Discovery in Databases
ECML PKDD 2016: Machine Learning and Knowledge Discovery in Databases
Conference Details: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), Riva del Garda, Italy, 19-23 September 2016
Appears in Collections:Insight Research Collection

Show full item record

SCOPUSTM   
Citations 50

1
Last Week
1
Last month
checked on Aug 9, 2018

Google ScholarTM

Check

Altmetric


This item is available under the Attribution-NonCommercial-NoDerivs 3.0 Ireland. No item may be reproduced for commercial purposes. For other possible restrictions on use please refer to the publisher's URL where this is made available, or to notes contained in the item itself. Other terms may apply.