@inproceedings{5054aceb113d4755b376c0bd6c0f330d,
title = "Topy: Real-time story tracking via social tags",
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).",
keywords = "News, Social media, Social tags, Story tracking",
author = "Gevorg Poghosyan and {Atif Qureshi}, M. and Georgiana Ifrim",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.; 15th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2016 ; Conference date: 19-09-2016 Through 23-09-2016",
year = "2016",
doi = "10.1007/978-3-319-46131-1_10",
language = "English",
isbn = "9783319461304",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "45--49",
editor = "Bj{\"o}rn Bringmann and Elisa Fromont and Nikolaj Tatti and Volker Tresp and Pauli Miettinen and Bettina Berendt and Gemma Garriga",
booktitle = "Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2016, Proceedings",
address = "Germany",
}