On the coherence of fake news articles

Iknoor Singh; Deepak Padmanabhan; Anoop Kadan

doi:10.1007/978-3-030-65965-3_42

On the coherence of fake news articles

Iknoor Singh, Deepak Padmanabhan^*, Anoop Kadan

^*Corresponding author for this work

School of Electronics, Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

51 Downloads (Pure)

Abstract

The generation and spread of fake news within new and online media sources is emerging as a phenomenon of high societal significance. Combating them using data-driven analytics has been attracting much recent scholarly interest. In this computational social science study, we analyze the textual coherence of fake news articles vis-a-vis legitimate ones. We develop three computational formulations of textual coherence drawing upon the state-of-the-art methods in natural language processing and data science. Two real-world datasets from widely different domains which have fake/legitimate article labellings are then analyzed with respect to textual coherence. We observe apparent differences in textual coherence across fake and legitimate news articles, with fake news articles consistently scoring lower on coherence as compared to legitimate news ones. While the relative coherence shortfall of fake news articles as compared to legitimate ones form the main observation from our study, we analyze several aspects of the differences and outline potential avenues of further inquiry.

Original language	English
Title of host publication	CML PKDD 2020 workshops: workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020: proceedings
Editors	Irena Koprinska, Michael Kamp, Annalisa Appice, Corrado Loglisci, Luiza Antonie, Albrecht Zimmermann, Riccardo Guidotti, Özlem Özgöbek, Rita P. Ribeiro, Ricard Gavaldà, João Gama, Linara Adilova, Yamuna Krishnamurthy, Pedro M. Ferreira, Donato Malerba, Ibéria Medeiros, Michelangelo Ceci, Giuseppe Manco, Elio Masciari , Zbigniew W. Ras, Peter Christen, Eirini Ntoutsi, Erich Schubert, Arthur Zimek, Anna Monreale, Przemyslaw Biecek, Salvatore Rinzivillo, Benjamin Kille, Andreas Lommatzsch, Jon Atle Gulla
Publisher	Springer Cham
Pages	591-607
ISBN (Electronic)	9783030659653
ISBN (Print)	9783030659646
DOIs	https://doi.org/10.1007/978-3-030-65965-3_42
Publication status	Published - 02 Feb 2021
Event	8th International Workshop on News Recommendation and Analytics (INRA 2020) - Duration: 14 Sept 2020 → 14 Sept 2020 https://www.ntnu.no/wiki/pages/viewpage.action?pageId=188580623

Publication series

Name	Communications in Computer and Information Science
Volume	1323
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Workshop

Workshop	8th International Workshop on News Recommendation and Analytics (INRA 2020)
Period	14/09/2020 → 14/09/2020
Internet address	https://www.ntnu.no/wiki/pages/viewpage.action?pageId=188580623

Access to Document

10.1007/978-3-030-65965-3_42Licence: CC BY

On the coherence of fake news articles
Copyright 2021 the authors. This is an open access paper published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
Final published version, 1.01 MBLicence: CC BY

Cite this

Singh, I., Padmanabhan, D., & Kadan, A. (2021). On the coherence of fake news articles. In I. Koprinska, M. Kamp, A. Appice, C. Loglisci, L. Antonie, A. Zimmermann, R. Guidotti, Ö. Özgöbek, R. P. Ribeiro, R. Gavaldà, J. Gama, L. Adilova, Y. Krishnamurthy, P. M. Ferreira, D. Malerba, I. Medeiros, M. Ceci, G. Manco, E. M., Z. W. Ras, P. Christen, E. Ntoutsi, E. Schubert, A. Zimek, A. Monreale, P. Biecek, S. Rinzivillo, B. Kille, A. Lommatzsch, ... J. A. Gulla (Eds.), CML PKDD 2020 workshops: workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020: proceedings (pp. 591-607). (Communications in Computer and Information Science; Vol. 1323). Springer Cham. https://doi.org/10.1007/978-3-030-65965-3_42

Singh, Iknoor ; Padmanabhan, Deepak ; Kadan, Anoop. / On the coherence of fake news articles. CML PKDD 2020 workshops: workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020: proceedings. editor / Irena Koprinska ; Michael Kamp ; Annalisa Appice ; Corrado Loglisci ; Luiza Antonie ; Albrecht Zimmermann ; Riccardo Guidotti ; Özlem Özgöbek ; Rita P. Ribeiro ; Ricard Gavaldà ; João Gama ; Linara Adilova ; Yamuna Krishnamurthy ; Pedro M. Ferreira ; Donato Malerba ; Ibéria Medeiros ; Michelangelo Ceci ; Giuseppe Manco ; Elio Masciari ; Zbigniew W. Ras ; Peter Christen ; Eirini Ntoutsi ; Erich Schubert ; Arthur Zimek ; Anna Monreale ; Przemyslaw Biecek ; Salvatore Rinzivillo ; Benjamin Kille ; Andreas Lommatzsch ; Jon Atle Gulla. Springer Cham, 2021. pp. 591-607 (Communications in Computer and Information Science).

@inproceedings{9821994ad01443908ce1201a30426c70,

title = "On the coherence of fake news articles",

abstract = "The generation and spread of fake news within new and online media sources is emerging as a phenomenon of high societal significance. Combating them using data-driven analytics has been attracting much recent scholarly interest. In this computational social science study, we analyze the textual coherence of fake news articles vis-a-vis legitimate ones. We develop three computational formulations of textual coherence drawing upon the state-of-the-art methods in natural language processing and data science. Two real-world datasets from widely different domains which have fake/legitimate article labellings are then analyzed with respect to textual coherence. We observe apparent differences in textual coherence across fake and legitimate news articles, with fake news articles consistently scoring lower on coherence as compared to legitimate news ones. While the relative coherence shortfall of fake news articles as compared to legitimate ones form the main observation from our study, we analyze several aspects of the differences and outline potential avenues of further inquiry.",

author = "Iknoor Singh and Deepak Padmanabhan and Anoop Kadan",

year = "2021",

month = feb,

day = "2",

doi = "10.1007/978-3-030-65965-3_42",

language = "English",

isbn = "9783030659646",

series = "Communications in Computer and Information Science",

publisher = "Springer Cham",

pages = "591--607",

editor = "Irena Koprinska and Michael Kamp and Annalisa Appice and Corrado Loglisci and Luiza Antonie and Albrecht Zimmermann and Riccardo Guidotti and {\"O}zlem {\"O}zg{\"o}bek and Ribeiro, {Rita P.} and Ricard Gavald{\`a} and Jo{\~a}o Gama and Linara Adilova and Yamuna Krishnamurthy and Ferreira, {Pedro M.} and Donato Malerba and Ib{\'e}ria Medeiros and Michelangelo Ceci and Giuseppe Manco and {Elio Masciari} and Ras, {Zbigniew W.} and Peter Christen and Eirini Ntoutsi and Erich Schubert and Arthur Zimek and Anna Monreale and Przemyslaw Biecek and Salvatore Rinzivillo and Benjamin Kille and Andreas Lommatzsch and Gulla, {Jon Atle}",

booktitle = "CML PKDD 2020 workshops: workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020: proceedings",

note = "8th International Workshop on News Recommendation and Analytics (INRA 2020) ; Conference date: 14-09-2020 Through 14-09-2020",

url = "https://www.ntnu.no/wiki/pages/viewpage.action?pageId=188580623",

}

Singh, I, Padmanabhan, D & Kadan, A 2021, On the coherence of fake news articles. in I Koprinska, M Kamp, A Appice, C Loglisci, L Antonie, A Zimmermann, R Guidotti, Ö Özgöbek, RP Ribeiro, R Gavaldà, J Gama, L Adilova, Y Krishnamurthy, PM Ferreira, D Malerba, I Medeiros, M Ceci, G Manco, EM, ZW Ras, P Christen, E Ntoutsi, E Schubert, A Zimek, A Monreale, P Biecek, S Rinzivillo, B Kille, A Lommatzsch & JA Gulla (eds), CML PKDD 2020 workshops: workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020: proceedings. Communications in Computer and Information Science, vol. 1323, Springer Cham, pp. 591-607, 8th International Workshop on News Recommendation and Analytics (INRA 2020), 14/09/2020. https://doi.org/10.1007/978-3-030-65965-3_42

On the coherence of fake news articles. / Singh, Iknoor; Padmanabhan, Deepak; Kadan, Anoop.
CML PKDD 2020 workshops: workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020: proceedings. ed. / Irena Koprinska; Michael Kamp; Annalisa Appice; Corrado Loglisci; Luiza Antonie; Albrecht Zimmermann; Riccardo Guidotti; Özlem Özgöbek; Rita P. Ribeiro; Ricard Gavaldà; João Gama; Linara Adilova; Yamuna Krishnamurthy; Pedro M. Ferreira; Donato Malerba; Ibéria Medeiros; Michelangelo Ceci; Giuseppe Manco; Elio Masciari; Zbigniew W. Ras; Peter Christen; Eirini Ntoutsi; Erich Schubert; Arthur Zimek; Anna Monreale; Przemyslaw Biecek; Salvatore Rinzivillo; Benjamin Kille; Andreas Lommatzsch; Jon Atle Gulla. Springer Cham, 2021. p. 591-607 (Communications in Computer and Information Science; Vol. 1323).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - On the coherence of fake news articles

AU - Singh, Iknoor

AU - Padmanabhan, Deepak

AU - Kadan, Anoop

PY - 2021/2/2

Y1 - 2021/2/2

N2 - The generation and spread of fake news within new and online media sources is emerging as a phenomenon of high societal significance. Combating them using data-driven analytics has been attracting much recent scholarly interest. In this computational social science study, we analyze the textual coherence of fake news articles vis-a-vis legitimate ones. We develop three computational formulations of textual coherence drawing upon the state-of-the-art methods in natural language processing and data science. Two real-world datasets from widely different domains which have fake/legitimate article labellings are then analyzed with respect to textual coherence. We observe apparent differences in textual coherence across fake and legitimate news articles, with fake news articles consistently scoring lower on coherence as compared to legitimate news ones. While the relative coherence shortfall of fake news articles as compared to legitimate ones form the main observation from our study, we analyze several aspects of the differences and outline potential avenues of further inquiry.

AB - The generation and spread of fake news within new and online media sources is emerging as a phenomenon of high societal significance. Combating them using data-driven analytics has been attracting much recent scholarly interest. In this computational social science study, we analyze the textual coherence of fake news articles vis-a-vis legitimate ones. We develop three computational formulations of textual coherence drawing upon the state-of-the-art methods in natural language processing and data science. Two real-world datasets from widely different domains which have fake/legitimate article labellings are then analyzed with respect to textual coherence. We observe apparent differences in textual coherence across fake and legitimate news articles, with fake news articles consistently scoring lower on coherence as compared to legitimate news ones. While the relative coherence shortfall of fake news articles as compared to legitimate ones form the main observation from our study, we analyze several aspects of the differences and outline potential avenues of further inquiry.

U2 - 10.1007/978-3-030-65965-3_42

DO - 10.1007/978-3-030-65965-3_42

M3 - Conference contribution

SN - 9783030659646

T3 - Communications in Computer and Information Science

SP - 591

EP - 607

BT - CML PKDD 2020 workshops: workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020: proceedings

A2 - Koprinska, Irena

A2 - Kamp, Michael

A2 - Appice, Annalisa

A2 - Loglisci, Corrado

A2 - Antonie, Luiza

A2 - Zimmermann, Albrecht

A2 - Guidotti, Riccardo

A2 - Özgöbek, Özlem

A2 - Ribeiro, Rita P.

A2 - Gavaldà, Ricard

A2 - Gama, João

A2 - Adilova, Linara

A2 - Krishnamurthy, Yamuna

A2 - Ferreira, Pedro M.

A2 - Malerba, Donato

A2 - Medeiros, Ibéria

A2 - Ceci, Michelangelo

A2 - Manco, Giuseppe

A2 - , Elio Masciari

A2 - Ras, Zbigniew W.

A2 - Christen, Peter

A2 - Ntoutsi, Eirini

A2 - Schubert, Erich

A2 - Zimek, Arthur

A2 - Monreale, Anna

A2 - Biecek, Przemyslaw

A2 - Rinzivillo, Salvatore

A2 - Kille, Benjamin

A2 - Lommatzsch, Andreas

A2 - Gulla, Jon Atle

PB - Springer Cham

T2 - 8th International Workshop on News Recommendation and Analytics (INRA 2020)

Y2 - 14 September 2020 through 14 September 2020

ER -

Singh I, Padmanabhan D, Kadan A. On the coherence of fake news articles. In Koprinska I, Kamp M, Appice A, Loglisci C, Antonie L, Zimmermann A, Guidotti R, Özgöbek Ö, Ribeiro RP, Gavaldà R, Gama J, Adilova L, Krishnamurthy Y, Ferreira PM, Malerba D, Medeiros I, Ceci M, Manco G, EM, Ras ZW, Christen P, Ntoutsi E, Schubert E, Zimek A, Monreale A, Biecek P, Rinzivillo S, Kille B, Lommatzsch A, Gulla JA, editors, CML PKDD 2020 workshops: workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020: proceedings. Springer Cham. 2021. p. 591-607. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-65965-3_42

On the coherence of fake news articles

Abstract

Publication series

Workshop

Access to Document

Fingerprint

Cite this