Automated Journalism as a Source of and a Diagnostic Device for Bias in Reporting

Autor: Leo Leppänen, Hanna Tuulonen, Stefanie Sirén-Heikel

Publikováno v: Media and Communication, Vol 8, Iss 3, Pp 39-49 (2020)

In this article we consider automated journalism from the perspective of bias in news text. We describe how systems for automated journalism could be biased in terms of both the information content and the lexical choices in the text, and what mechan

Externí odkaz: https://doaj.org/article/95c1f851845e4b499782dc9d09978e73

Personal Research Assistant for Online Exploration of Historical News

Autor: Hannu Toivonen, Lidia Pivovarova, Mark Granroth-Wilding, Khalid Alnajjar, Elaine Zosa, Axel Jean-Caurant, Jari Avikainen, Leo Leppänen

Publikováno v: Advances in Information Retrieval
Lecture Notes in Computer Science ISBN: 9783030454418
ECIR (2)
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Advances in Information Retrieval

Demostration paper We present a novel environment for exploratory search in large collections of historical newspapers developed as a part of the News- Eye project. In this paper we focus on the intelligent Personal Research Assistant (PRA) component

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d0305e6975cc7814de3a0d102e5445f8
http://europepmc.org/articles/PMC7148060

A Baseline Document Planning Method for Automated Journalism

Autor: Leo Leppänen, Hannu Toivonen

Publikováno v: University of Helsinki

In this work, we present a method for content selection and document planning for automated news and report generation from structured statistical data such as that offered by the European Union’s statistical agency, Eurostat. The method is driven

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49764b3e7f610e47270daa3ea31adc57

Recycling a genre for news automation: The production of Valtteri the Election Bot

Autor: Leo Leppänen, Lauri Haapanen

The amount of available digital data is increasing at a tremendous rate. These data, however, are of limited use unless converted into a user-friendly form. We took on this task and built a natural language generation (NLG) driven system that generat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a41e44b3c365eec7abdb9fcddf3c6edf
https://zenodo.org/record/4095140

No Landslide for the Human Journalist - An Empirical Study of Computer-Generated Election News in Finland

Autor: Myriam Munezero, Hannu Toivonen, Leo Leppänen, Caj Södergård, Magnus Melin, Asta Bäck

Publikováno v: Melin, M, Bäck, A, Södergård, C, Munezero, M & Leppänen, L 2018, ' No landslide for the human journalist : An empirical study of computer-generated election news in Finland ', IEEE Access, vol. 6, 8424161, pp. 43356-43367 . https://doi.org/10.1109/ACCESS.2018.2861987
IEEE Access, Vol 6, Pp 43356-43367 (2018)

In an age of struggling news media, automated generation of news via natural language generation (NLG) methods could be of great help, especially in areas where the amount of raw input data is big, and the structure of the data is known in advance. O

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b91d74f09dab79a3bebd94fd62e41067
https://doi.org/10.1109/access.2018.2861987