What’s in the news? Identification of trending topics in alternative and mainstream Lithuanian media

Mandravickaitė, Justina; Briedienė, Monika; Uus, Jonas; Krilavičius, Tomas

Use this url to cite publication: https://hdl.handle.net/20.500.12259/119629

What’s in the news? Identification of trending topics in alternative and mainstream Lithuanian media

Type of publication

Straipsnis konferencijos medžiagoje Scopus duomenų bazėje / Article in conference proceedings in Scopus database (P1a2)

Author(s)

Author	Affiliation
Mandravickaitė, Justina	Baltijos pažangiųjų technologijų institutas	LT
Briedienė, Monika	Informatikos fakultetas / Faculty of Informatics	LT
Uus, Jonas	Baltijos pažangiųjų technologijų institutas	LT
Krilavičius, Tomas	Baltijos pažangių technologijų institutas	LT

Title

What’s in the news? Identification of trending topics in alternative and mainstream Lithuanian media

[en]

Is part of

CEUR Workshop proceedings [electronic resource]: Machine learning for trend and weak signal detection in social networks and social media, Toulouse, France, February 27-28, 2020 : proceedings. Aachen : CEUR-WS, 2020, Vol. 2606

Date Issued

Date
2020

Publisher

Aachen : CEUR-WS

Is Referenced by

Scopus

Extent

p. 3-17

URI

URI
https://www.vdu.lt/cris/bitstream/20.500.12259/119629/2/ISSN1613-0073_2020_V_2606.PG_3-17.pdf
https://hdl.handle.net/20.500.12259/119629

Field of Science

Informatikos inžineri...

Komunikacija ir infor...

Informatika / Inform...

Keywords (en)

Topic modelling

Framing

Media Monitoring

NLP

Lithuanian language

Artificial Intelligen...

LDA

Stm

Abstract (en)

It is no longer surprising that internet media is a significant appliance in reflecting and shaping public opinion. Tracking topics dynamics and focus in different media channels is an important tool for opinion-forming mechanisms and process analysis. Information collect, text analytics and Artificial Intelligence tools allows identification of trending topics in different media sources, while exploratory visual analytics tools provide means to identify prevalence of topics in different sources, and their dynamics. In this paper we discuss an ongoing research and demonstrate applicability of such approach to main Lithuanian news portal (delfi.lt) and alternative unconventional media channels – sarmatas.lt and netiesa.lt.