Information flow between news articles: Slovene media case study

Jan Chołoniewski , Leban Gregor , Macek Sebastijan , Rehar Aljoša

Abstract

We present results of a study on usage of text similarity measures based on co-occurrence of words and phrases to classify a relation between a pair of news articles (i.e. no relation, both based on a common source, one based on the other). For each Slovenian article written in Slovene and published online on 27th June 2016, we found the most similar release from the Slovenian Press Agency (STA) database to obtain a list of candidate article-source pairs. Four experts from STA were asked to score the pairs, and their annotations were used to train classifiers and evaluate their accuracy.
Publication typeOriginal work published as abstract
Author Jan Chołoniewski PFENS
Jan Chołoniewski,,
- Center of Physics in Economics and Social Sciences
, Leban Gregor
Leban Gregor,,
-
, Macek Sebastijan
Macek Sebastijan,,
-
, Rehar Aljoša
Rehar Aljoša,,
-
Journal seriesInformatica. An International Journal of Computing and Informatics, ISSN 0350-5596
Issue year2016
VolD
Pages13-16
Publication size in sheets0.5
ConferenceConference on Data Mining and Data Warehouses (SiKDD 2016), 10-10-2016 - 10-10-2016, Ljubliana, Słowenia
URL http://ailab.ijs.si/dunja/SiKDD2016/Papers/Choloniewski_InformationFlow.pdf
projectReverse EngiNeering of sOcial Information pRocessing. Project leader: Hołyst Janusz, , Phone: 22 234 7133, application date 28-04-2015, start date 01-01-2016, end date 31-12-2019, 691152, Implemented
WF Horizon 2020 [Horyzont 2020]
[ H2020-MSCA-RISE-2015 POL] Inżynieria odwrotna przetwarzania informacji społecznej. . Project leader: Hołyst Janusz, , Phone: 22 234 7133, application date 16-09-2015, start date 01-10-2015, planned end date 31-12-2015, Implemented
WF Projekty finansowane przez MNiSW
Languageen angielski
File
choloniewski-sikdd2016-detecting_information_flow.pdf / 182.06 KB / choloniewski-sikdd2016-detecting_information_flow.pdf 182.06 KB
Score (nominal)0
ScoreMinisterial score = 0.0, 28-11-2017, ArticleFromJournal
Ministerial score (2013-2016) = 5.0, 28-11-2017, ArticleFromJournal - czasopismo zagraniczne spoza list
Citation count*0
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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